Upload your K9 results

[John Doe]

Davidski has made a new test called K9, here are the results he sent me:

K9

Oceanian-0.05 or 0.5%

European (WHG I suppose)-0.192158 or 19%

EEF-0.520595 or 52%

East_Asian-0.007275 or noise

South_Asian-0.05 0.5%

Central_Asian-0.256318 (ANE I suppose) or 26%

Amerindian-0.000144 or noise

Siberian-0.007463 or noise

Sub-Saharan-0.016027 or 1.6%

[J Man]

Here are mine.

K9

Oceanian-0.9%

European-46.0%

EEF-28.4%

East_Asian-1.3%

South_Asian-0.4%

Central_Asian-21.1%

Amerindian-0.7%

Siberia-0.8%

Sub-Saharan-0.0%

[Krefter]

Here are mine. Everything makes sense except the South Asian. My Euro score seems a bit low, and isn't consitent with me scoring 40% WHG in ANE K8.



Euro
EEF
Central Asian
Ameridian
South Asian
Sub Saharan
Oceanian
Siberian
East Asian


42.6072
37.1255
12.5055

3.2677

2.2964

1.4561

0.4687

0.2718

0.001




Me and J Man had near identical ANE K8 scores but have very differnt Teal_K9 scores. My guess is because more of his ENF is expressed via Central Asian, because of Finnish and Italian ancestry. More of my ENF is expressed via EEF because of Spanish and West-South German ancestry.

[MfA]

.....

[Sapporo]

Based on fst distances, South Asian component is heavily ANE mixed as I presumed. 0.076 to Central Asian, 0.082 to East Asian, 0.084 to EEF, 0.086 to European, 0.092 to Siberian and 0.126 to Amerindian.

https://docs.google.com/spreadsheets/d/1SFjUKWl6ltft32UDjh9LKceS4VAGhpbAVXqPbhrfaSs/edit#gid=825863363

[Krefter]

Based on fst distances, South Asian component is heavily ANE mixed as I presumed. 0.076 to Central Asian, 0.082 to East Asian, 0.084 to EEF, 0.086 to European, 0.092 to Siberian and 0.126 to Amerindian.

https://docs.google.com/spreadsheets/d/1SFjUKWl6ltft32UDjh9LKceS4VAGhpbAVXqPbhrfaSs/edit#gid=825863363

The K9 South Asian component scored 23-28% ANE in ANE K8. Davidski posted the scores once in his blog.

[Dr_McNinja]

The K9 South Asian component scored 23-28% ANE in ANE K8. Davidski posted the scores once in his blog.https://docs.google.com/spreadsheets/d/1q_rkm8UwyE0KOpyEzqAmAIeFh7cMUipvDPwqqcEONQM/edit#gid=962519559

Very close to Harappa S-Indian but that had more ENF:

23.65% ANE
22.01% ASE
0.06% WHG-UHG
9.03% East_Eurasian
0.70% West_African
5.54% East_African
39.01% ENF

This was in K7 though.

I'm surprised this component is registering so highly in South Asians

[J Man]

Here are mine. Everything makes sense except the South Asian. My Euro score seems a bit low, and isn't consitent with me scoring 40% WHG in ANE K8.



Euro
EEF
Central Asian
Ameridian
South Asian
Sub Saharan
Oceanian
Siberian
East Asian


42.6072
37.1255
12.5055

3.2677

2.2964

1.4561

0.4687

0.2718

0.001




Me and J Man had near identical ANE K8 scores but have very differnt Teal_K9 scores. My guess is because more of his ENF is expressed via Central Asian, because of Finnish and Italian ancestry. More of my ENF is expressed via EEF because of Spanish and West-South German ancestry.

Your results look quite accurate to me. This looks like quite a good test overall actually. The main likely reason as you say is probably because more of my ENF ancestry is being expressed by the Central_Asian component whereas yours is being expressed more so by the EEF component. Also it could be that I score more ANE than you do on the K8 as well. That could also be related to my higher overall European score to a degree at least as ANE is also linked to EHG.

[Krefter]

Also it could be that I score more ANE than you do on the K8 as well. That could also be related to my higher overall European score to a degree at least as ANE is also linked to EHG.

That makes sense. ~1% of my ANE is of Native American origin, so you have like 3% more Eurasian ANE than me. Also, K9 shows geographic trends because now the components are a mixture of K8 components.

[Dr_McNinja]

https://docs.google.com/spreadsheets/d/1q_rkm8UwyE0KOpyEzqAmAIeFh7cMUipvDPwqqcEONQM/edit#gid=962519559

Very close to Harappa S-Indian but that had more ENF:

23.65% ANE
22.01% ASE
0.06% WHG-UHG
9.03% East_Eurasian
0.70% West_African
5.54% East_African
39.01% ENF

This was in K7 though.

I'm surprised this component is registering so highly in South Asians

Going by the K8 results, I'd estimate 60-70% South Asian for myself and I'd expect 40% Central Asian but some would go into European, Siberian, etc.

I had 16.7% ASE and ~4% Oceanian in K8 so that corresponds to 58% and 48% K9 South Asian. There seems to be heavy drift towards India though. A lot of Oceanian and European are both being left over in the South and North so it's probably eating up most of the ANE/ENF.

[Gray Fox]

Is there a fee for him to perform this run??

[SwampThing27]

Did you guys email him about this test or did he just send them to people he did the K8 on? I'm probably not cool enough.

[Sapporo]

Going by the K8 results, I'd estimate 60-70% South Asian for myself and I'd expect 40% Central Asian but some would go into European, Siberian, etc.

I had 16.7% ASE and ~4% Oceanian in K8 so that corresponds to 58% and 48% K9 South Asian. There seems to be heavy drift towards India though. A lot of Oceanian and European are both being left over in the South and North so it's probably eating up most of the ANE/ENF.

https://docs.google.com/spreadsheets/d/1M2drQQD7jvwwaTkpFTuBLQXllkUTVNOIfa9FReH7V5M/edit#gid=27797479

UP Brahmins are around 50-55% South Asian on K9. I would estimate you wouldn't be higher than mid 40's. HGDP Pashtuns are between 28-38% for the most part. I'd guess I am around 38-40% myself.

[BalkanKiwi]

Did you guys email him about this test or did he just send them to people he did the K8 on? I'm probably not cool enough.

I paid for the K8 and haven't got results so I'm probably not cool enough either.

[Krefter]

deleted at member's request

Where'd you get the oracle?

[ZephyrousMandaru]

deleted at member's request

How did you do this?

[ZephyrousMandaru]

I'm guessing he used the Oracle-4 originally used for the Ancient Genomes analysis. I tried copying the contents of the spreadsheet into a Notepad document, but I was unable to do so. I'm guessing it had someone to do with the format, there has to be a way to replace the decimal point with a comma for all reference population. But I don't know how to.

[BalkanKiwi]

Oceanian 0.006966
European 0.499116
EEF 0.309471
East_Asian 0.00001
South_Asian 0.00001
Central_Asian 0.175034
Amerindian 0.009373
Siberian 0.00001
Sub-Saharan 0.00001

[Generalissimo]

Oceanian 0.006966
European 0.499116
EEF 0.309471
East_Asian 0.00001
South_Asian 0.175034
Central_Asian 0.00001
Amerindian 0.009373
Siberian 0.00001
Sub-Saharan 0.00001

It looks like South Asian should be Central Asian.

[Rukha]

Oceanian 0.000166
EEF 0.097034
European 0.146194
Amerindian 0.027393
Central_Asian 0.470917
South_Asian 0.233116
East_Asian 0.003198
Siberian 0.018239
Sub-Saharan 0.003743

[Dr_McNinja]

HRP0341 Punjabi Jatt Sikh

0% Oceanian
2.83% EEF
11.61% European
1.06% Amerindian
43.11% Central Asian
39.77% South Asian
0% East Asian
1.61% Siberian
0% SSA

HRP0349 (Me)

0.19% Oceanian
5.86% EEF
8.72% European
2.10% Amerindian
34.45% Central Asian
47.73% South Asian
0% East Asian
0.95% Siberian
0% SSA

HRP0393 Haryana Jatt

0% Oceanian
3.07% EEF
16.34% European
1.62% Amerindian
38.28% Central Asian
39.82% South Asian
0% East Asian
0.87% Siberian
0% SSA

HRP0370 Afghan Pashtun

0% Oceanian
13.16% EEF
13.91% European
1.20% Amerindian
46.11% Central Asian
23.32% South Asian
0% East Asian
2.08% Siberian
0.22% SSA

[Anabasis]

It seems i am combination of two component.

Oceanian 0,00001
EEF 0,458997
European 0,00001
Amerindian 0,00001
Central_Asian 0,540933
South_Asian 0,00001
East_Asian 0,00001
Siberian 0,00001
Sub-Saharan 0,00001

[Dr_McNinja]

https://docs.google.com/spreadsheets/d/1M2drQQD7jvwwaTkpFTuBLQXllkUTVNOIfa9FReH7V5M/edit#gid=27797479

UP Brahmins are around 50-55% South Asian on K9. I would estimate you wouldn't be higher than mid 40's. HGDP Pashtuns are between 28-38% for the most part. I'd guess I am around 38-40% myself.

Good guesses. Yours was ~40 and mine was ~48. Mine was the number predicted by my K8 Oceanian.

[surbakhunWeesste]

Oceanian 0.006582
European 0.09646
EEF 0.110458
East_Asian 0.01904
South_Asian 0.20775
Central_Asian 0.52418
Amerindian 0.003033
Siberian 0.032487
Sub-Saharan 1E-005

[jesus]

Oceanian 0.005857
European 0.012981
EEF 0.328508
East_Asian 1E-005
South_Asian 0.143712
Central_Asian 0.43027
Amerindian 0.020237
Siberian 1E-005
Sub-Saharan 0.058415

Vs Yamnaya K6


Yamnaya_related 0.161401
WHG_extra 0.0178
ENA 0.059369
Middle_Eastern 0.65434
Pre-Yamnaya 0.055206
Sub-Saharan 0.051884

I wonder if the 2% Amerindian is Yamnaya related. The two Yamnaya samples are 3% and 5% Amerindian.

[John Doe]

deleted at member's request

How do you get the K9 Oracle?

[John Doe]

Is there a fee for him to perform this run??

You need to donate around 20$ via Paypal to him via crowdfunding donation and then send your raw data to him, he'll then send you your results whenever a new test becomes available, check his website at Eurogenes for more info.

[John Doe]

Guys. You need to request the K9 from David. He doesn't automatically send it out to people. And I think he would only send it out to people who donated from before. I'm not sure though, you would need to ask him yourselves. Regarding the oracle, Anabasis on here did it for me.

David sent me my results without me asking him. Thanks. :)

[Salkin]

Mine:

Papuan - 0.3756%
EEF - 25.1987%
European - 56.7866%
Amerindian - 1.2962%
Central Asian - 14.9786%
South Asian - 1.0661%
East Asian - [noise]
Siberian - 0.2963%
Sub-Saharan - [noise]

[Helgenes50]

My K9 results


European 48.77 %
EEF 36.08 %
Central_Asian 13.94 %
Amerindian 0.8 %
Sub-Saharan 0.37 %
Oceanian 0%
East_Asian 0%
South_Asian 0%
Siberian 0 %

Like Jesus, I wonder if the Amerindian component ( 0.8 % in my case) is Yamnaya related,
This one is certainly more EHG (Karelian related) than SHG

[BalkanKiwi]

It looks like South Asian should be Central Asian.

Good pick up. Corrected.

[SwampThing27]

Oceanian 0.006966
European 0.499116
EEF 0.309471
East_Asian 0.00001
South_Asian 0.00001
Central_Asian 0.175034
Amerindian 0.009373
Siberian 0.00001
Sub-Saharan 0.00001

Did you email him to get your results?

[BalkanKiwi]

Did you email him to get your results?

Yeah I just asked him. I've paid for the K8 previously so he still had my data on file. I don't know if that means for any future calculators he doesn't release publicly you must have paid him in order for him to run your data.

[SwampThing27]

Yeah I just asked him. I've paid for the K8 previously so he still had my data on file. I don't know if that means for any future calculators he doesn't release publicly you must have paid him in order for him to run your data.

Yes I have paid him too for the K8 back when it was released so I just emailed him and asked about it.

[Ignis90]

That South Asian component is interesting. I score 3.9% despite being 0% ANE and 0% Yamnaya-related.

I've also 5.1% Central Asian and 1.3% Siberian, which added to my South Asian equal ~10%. I won't take these literally as they may hint to something more blurry like a basal thing.

I'm mainly EEF[-like] nonetheless, as expected (58.1%).

[kenji.aryan]

................

[John Doe]

Davidski has made a new test called K9, here are the results he sent me:

K9

Oceanian-0.05 or 0.5%

European (WHG I suppose)-0.192158 or 19%

EEF-0.520595 or 52%

East_Asian-0.007275 or noise

South_Asian-0.05 0.5%

Central_Asian-0.256318 (ANE I suppose) or 26%

Amerindian-0.000144 or noise

Siberian-0.007463 or noise

Sub-Saharan-0.016027 or 1.6%


Oracle K9

K9 Oracle
1- [email protected] 1,79493986096744
2- [email protected] 1,96549842604872
3- [email protected] 2,68213368716649
4- [email protected] 3,3995601884196
5- [email protected] 3,41132532926224
6- [email protected] 5,60260583573617
7- [email protected] 6,98255882008433
8- [email protected] 7,61575233435749
9- [email protected] 8,40370446762553
10- [email protected] 10,4793327858801
11- [email protected] 10,7799141811867
12- [email protected] 11,877869150065
13- [email protected] 13,0573894220114
14- [email protected] 14,4041602206348
15- [email protected] 14,7199733346248
16- [email protected] 15,427184679882
17- [email protected] 15,484295955082
18- [email protected] 17,3793707113711
19- [email protected] 19,019100010487
20- [email protected] 19,2165968795965
21- [email protected] 20,40412992713
22- [email protected] 20,5885567716558
23- [email protected] 20,8309778082575

[BalkanKiwi]

Oceanian 0.006966
European 0.499116
EEF 0.309471
East_Asian 0.00001
South_Asian 0.00001
Central_Asian 0.175034
Amerindian 0.009373
Siberian 0.00001
Sub-Saharan 0.00001

Oracle:

[email protected] 1,8431984375536
[email protected] 3,59465103475983
[email protected] 3,61771656219431
[email protected] 3,71553891540313
[email protected] 5,02333450807329
[email protected] 6,33803641706957
[email protected] 6,88382358674326
[email protected] 6,90665836598279
[email protected] 7,43649465848158
[email protected] 7,93189824503567
[email protected] 8,29401245419316
[email protected] 8,53251497156612
[email protected] 8,80113014030963
[email protected] 8,88496327634906
[email protected] 9,93772210720344
[email protected] 10,1529099060319
[email protected] 10,153028325998
[email protected] 11,5119347423008
[email protected] 11,7760646320476
[email protected] 12,4874022946368

[SwampThing27]

Got my results today. Could anyone do an oracle run on them? Looking at tghe reference sheet i probably fall along side the English like usual.

Oceanian 0.003606
European 0.489054
EEF 0.318246
East_Asian .00001
South_Asian 0.021088
Central_Asian 0.155131
Amerindian 0.002273
Siberian .00001
Sub-Saharan 0.010581

[Wulf Warrior]

Oceanian 0.00001
European 0.531933
EEF 0.271178
East_Asian 0.00001
South_Asian 0.00001
Central_Asian 0.181729
Amerindian 0.009691
Siberian 0.005429
Sub-Saharan 0.00001

[email protected] 1,09506579710993
[email protected] 2,12661151602732
[email protected] 2,3142771461895
[email protected] 2,36435137089847
[email protected] 2,53195211678658
6-Ukrainia[email protected] 3,94827651027635
[email protected] 3,99609550436423
[email protected] 4,83835993286981
[email protected] 5,31461778495876
[email protected] 5,35841862772964
[email protected] 6,24706526064365
[email protected] 6,4968787171639
[email protected] 7,21904895757573
[email protected] 7,56763101783511
[email protected] 9,74752241745563
[email protected] 11,2958685689238
[email protected] 11,4270446372028
[email protected] 11,9201311221386
[email protected] 12,3468477398079
[email protected] 13,4079883606751

[NK19191]

Oceanian 0.004253
European 0.066553
EEF 0.335556
East_Asian 0.003603
South_Asian 0.09904
Central_Asian 0.464166
Amerindian 1E-005
Siberian 0.023141
Sub-Saharan 0.003677

[email protected] 3,94568276320082
[email protected] 6,32617484890268
[email protected] 13,0356302483039
[email protected] 13,6431967650005
[email protected] 14,2360619340241
[email protected] 14,8049307971534
[email protected] 15,2652015865177
[email protected] 15,4945004278421
[email protected] 15,5021267966343
[email protected] 15,68318945911
[email protected] 16,043107189355
12-Turk [email protected] 16,2462172738954
[email protected] 17,620808162255
[email protected] 18,1229062395959
[email protected] 18,5456899918289
[email protected] 20,8361834393997
[email protected] 20,9938747962465
[email protected] 21,4856563544535
[email protected] 22,236694090921
[email protected] 22,9611914929935

[falconson1]

Hello, just joined Anthrogenica. Trying to get up to speed, although I am a seasoned genetic genealogist (2001).

K9 results from Eurogenes in Gedmatch do not use the same population groups. Are the results you are posting coming from another source?

I am a Eurogenes project member and have been since day 1. As I recall, I am CA4.

Any clarification here would be appreciated.

[CelticGerman]

Hello, just joined Anthrogenica. Trying to get up to speed, although I am a seasoned genetic genealogist (2001).

K9 results from Eurogenes in Gedmatch do not use the same population groups. Are the results you are posting coming from another source?

I am a Eurogenes project member and have been since day 1. As I recall, I am CA4.

Any clarification here would be appreciated.


Send an e-mail to David. He will probably reply very quickly. However, I am not sure he is doing it for everybody. Maybe it's only for those having contributed with some money before (crowdfunding Eurasia K8). You should ask for K6 and K9.

[Krefter]

Can someone do an Oracle with my K9 results?



Euro
EEF
Amerindian
Central Asian
South Asian
Sub Saharan
Oceanian
Siberian
East Asian


42.6072
37.1255
3.2677
12.5055
2.2964
1.4561
0.4687
0.2718
0.001

[Dr_McNinja]

Can someone share the data text file for the Oracle?

[Anabasis]

Can someone share the data text file for the Oracle?


K9 Teal Oracle Worksheet. paste your results into INPUT area with not using (dot) but (comma) as decimal separator.

https://drive.google.com/file/d/0Bx9OviX7j0B2RUVpb05uU0xwdVU/view?usp=sharing

[CelticGerman]

my result4292

my uncle paternal side4293

my uncle maternal side4294

[CelticGerman]

and here comes the two French of the family (father and daughter):

42954296

[Rukha]

Thanks to Anabasis and noel.

[email protected] 9,9605622231033
[email protected] 11,4590933274263
[email protected] 11,5598934194944
[email protected] 12,3462077343359
[email protected] 14,1807596436462
[email protected] 14,2139369181811
[email protected] 14,5633631943741
[email protected] 16,8591025494479
[email protected] 16,9481614291816
[email protected] 25,3838172278718
[email protected] 25,7585169723348
[email protected] 26,4091771448807
[email protected] 27,22172826594
[email protected] 28,3123217946516
[email protected] 28,5569527972498
[email protected] 28,7272467646322
[email protected] 28,7464458693314
[email protected] 30,6231591907534
[email protected] 31,0577607811856
[email protected] 31,1952668579251

[SwampThing27]

K9 Teal Oracle Worksheet. paste your results into INPUT area with not using (dot) but (comma) as decimal separator.

https://drive.google.com/file/d/0Bx9OviX7j0B2RUVpb05uU0xwdVU/view?usp=sharing

Thanks!

My results, pretty much as expected:

[email protected] 2.9767022689883
[email protected] 5.19981634789874
[email protected] 5.32654541136889
[email protected] 6.04197702724033
[email protected] 6.90500617016379
[email protected] 7.29988126563714
[email protected] 7.32204119295506
[email protected] 7.81775049653672
[email protected] 8.05401111252182
[email protected] 8.50699298930412
[email protected] 8.73460106759318
[email protected] 8.778282317419
[email protected] 9.98576828741785
[email protected] 10.1578540912734
[email protected] 10.953948168735
[email protected] 11.6475221351836
[email protected] 11.8900501975391
[email protected] 12.2872564251959
[email protected] 13.2525827557734
[email protected] 13.4746738817373

[Arbogan]

I bet i'll outteal everyone else, save for the south-central asians here. :D Kidding. But I'd be surprised if i score any WHG on this test. Now that whatever this Caucasus-Iranian-South-central asian componential grouping is becoming better defined thanks to Davids efforts.

[MfA]

I bet i'll outteal everyone else, save for the south-central asians here. :D

Yeah i bet you would.
This one is a Kurd from Adana (Adana23113), We know Lak Kurds are deported there at some time of history and he has quite many teal, also relatively low European.

Oceanian 0.77%
Central_Asian 52.36%
European 3.71%
Amerindian 0.94%
South_Asian 5.42%
EEF 35.64%
East_Asian 0.54%
Siberian 0.62%
Sub-Saharan 0.00%

[Arbogan]

Yeah i bet you would.
This one is a Kurd from Adana (Adana23113), We know Lak Kurds are deported there at some time of history and he has quite many teal, also relatively low European.

Oceanian 0.77%
Central_Asian 52.36%
European 3.71%
Amerindian 0.94%
South_Asian 5.42%
EEF 35.64%
East_Asian 0.54%
Siberian 0.62%
Sub-Saharan 0.00%

I think it's because Ilam-loorestan is a resvoir of pre-iranian populations in western iran. I think pishti-i-kuh lurs are certainly good proxys for kassaites and other pre-iranian nomads. Especially loorestan has losts of bronze and pre-bronze age graves.

[Dr_McNinja]

I stuck the leftover (everything outside of South Asian and Central Asian) into the Oracle and got this:

HRP0393 Haryana Jatt


21.91%

[email protected] 20.034333298116
[email protected] 20.134422265116
[email protected] 23.4628247632569
[email protected] 23.6775248321546
[email protected] 24.9649144076119
[email protected] 25.1819137989947
[email protected] 28.2290568485736
8-Neolithic_[email protected] 28.7274057499542
[email protected] 28.8260965359516
[email protected] 29.2526783519062
[email protected] 29.3376911805974
[email protected] 29.5991496643924
[email protected] 29.8178918838182
[email protected] 30.0734475519868
[email protected] 30.7395408126211
[email protected] 30.9824359570064
[email protected] 31.3781040279384
[email protected] 31.6287562705207
[email protected] 32.2863075309701
[email protected] 32.3063744569087


Me


17.82%

[email protected] 17.5553120285571
[email protected] 17.9539306037007
[email protected] 20.1803022878067
[email protected] 20.8080617892729
[email protected] 21.1559452214468
[email protected] 21.2967435433214
[email protected] 21.4292008480105
[email protected] 21.7190397707183
[email protected] 22.1564815090777
[email protected] 22.6243637528219
[email protected] 22.8362579697668
[email protected] 22.987341702772
[email protected] 23.3210651886872
[email protected] 23.3511557071101
[email protected] 24.2753473955225
[email protected] 24.2850477715486
[email protected] 25.2531146575155
[email protected] 25.659366173497
[email protected] 26.0500393219341
[email protected] 26.4068203657691


HRP0341 Punjabi Jatt Sikh


17.12%

[email protected] 20.5245601089305
[email protected] 21.4277561557738
[email protected] 22.2863436341025
[email protected] 23.8307215155144
[email protected] 24.5174027286742
[email protected] 24.6724851747853
[email protected] 25.0147486519953
[email protected] 25.0314334558591
[email protected] 25.8411737245447
[email protected] 25.85368183119
[email protected] 25.9660397518845
[email protected] 26.0263663312438
[email protected] 26.8787216751118
[email protected] 27.1005517761318
[email protected] 27.3971133302397
[email protected] 27.5019942771429
[email protected] 27.8525547927722
[email protected] 28.2060958757145
[email protected] 28.5156002155536
[email protected] 28.768525725619


Kenji (Himachal Pradesh Brahmin)


16.98%

[email protected] 25.3464745647615
[email protected] 25.4743699133929
[email protected] 25.859547046037
[email protected] 25.8605093134458
[email protected] 25.9009604177142
[email protected] 26.0349079230509
[email protected] 26.1464542227048
[email protected] 26.1724122927177
[email protected] 26.6159404353425
[email protected] 26.7298237958109
[email protected] 27.0088912600555
[email protected] 27.1931928583239
[email protected] 27.2085117201511
[email protected] 27.3309554247058
[email protected] 27.360668707517
[email protected] 27.6043199678624
[email protected] 27.7235254946649
[email protected] 28.0901348342812
[email protected] 28.1303612428508
[email protected] 28.1694194221014


HRP0370 Afghan Pashtun


30.57%

[email protected] 10.3694045805781
[email protected] 10.579050824625
[email protected] 10.8031272927234
[email protected] 14.6475235726676
[email protected] 15.3081942246628
[email protected] 17.1202842845209
[email protected] 17.8077524163635
[email protected] 22.1174309273523
[email protected] 22.5776280860412
[email protected] 23.5559845573561
[email protected] 24.1905028786598
[email protected] 24.2484584867652
[email protected] 24.304827117725
[email protected] 24.3395322603853
[email protected] 24.8047329537253
[email protected] 25.7926145684053
[email protected] 25.9191473289941
[email protected] 25.9278934204073
[email protected] 25.9826737549795
[email protected] 26.2266054397008


Afghan Pashtun (zahra)


26.81%

[email protected] 18.4871445302984
[email protected] 18.6914991582881
[email protected] 19.5905010540823
4-Bas[email protected] 20.2235141460107
[email protected] 22.5771310216333
[email protected] 23.1051942282451
[email protected] 23.8639215222478
[email protected] 26.0234320388935
[email protected] 26.2040145088418
[email protected] 26.4486072408909
[email protected] 26.6068254782979
[email protected] 26.8974907689621
[email protected] 27.0618756914264
[email protected] 27.1747561813563
[email protected] 27.5947273130637
[email protected] 27.6427102197196
[email protected] 27.831172853576
[email protected] 28.0038725326731
[email protected] 28.3045351219994
[email protected] 28.4222284654279
Rukha's breakdown was almost identical to mine so his would be the same.

[surbakhunWeesste]

pretty interesting

[email protected] 8.95043215679184
[email protected] 10.3673780029897
[email protected] 14.7045336161553
[email protected] 14.739228326402
[email protected] 15.7675750942749
[email protected] 15.900579229109
[email protected] 17.5110124877347
[email protected] 17.5870177434607
[email protected] 18.8395289304497
[email protected] 23.098494164021
[email protected] 24.1675876782456
[email protected] 24.9660377482334
[email protected] 25.5276956420347
[email protected] 25.7255831708127
[email protected] 25.7681376971986
[email protected] 28.0332800246033
[email protected] 28.4146869550709
[email protected] 29.7972595531369
[email protected] 30.2951171907619
[email protected] 30.6888962524812

1-50

36 Brahui 8.950432157
24 Balochi 10.367378
87 Kalash 14.70453362
176 Tajik_Pomiri 14.73922833
145 Pathan 15.76757509
175 Tadjik 15.90057923
5 Afghan_Uzbeki 17.51101249
3 Afghan_Tadjik 17.58701774
39 Burusho 18.83952893
107 Lezgin 23.09849416
43 Chechen 24.16758768
97 Kumyk 24.96603775
2 Adygei 25.52769564
138 North_Ossetian 25.72558317
23 Balkar 25.7681377
81 Iranian 28.03328002
184 Turkmen 28.41468696
1 Abkhasian 29.79725955
72 GujaratiA 30.29511719
136 Nogay 30.68889625
98 Kurdish 30.78149308
135 Nogai 30.93573545
69 Georgian 32.41245657
4 Afghan_Turkmen 32.45587189
194 Uzbek 33.54441186
195 Uzbeki 35.10498869
182 Turkish 36.53745323
73 GujaratiB 37.52222491
11 Armenian 39.27628769
83 Iranian_Jewish 40.00776265
35 Brahmin_UP 40.38506271
206 Turk Trabzon 41.41443219
34 Brahmin_TN 41.75290921
96 Kshatriya 42.46370128
13 Assyrian 43.19728118
82 Iranian_Jew 43.49993364
193 Uygur 44.48979806
74 GujaratiC 46.3371504
200 Yamnaya 46.38973531
85 Iraqi_Jewish 46.58817987
84 Iraqi_Jew 47.08110491
174 Syrian 47.28108126
106 Lebanese_Muslim 48.33970816
104 Lebanese 49.24367819
111 MA1 50.21783897
196 Velamas 50.69510731
86 Jordanian 51.18767524
46 Corded_Ware_LN 51.25034242
37 Bulgarian 51.5812446

[Arbogan]

pretty interesting

[email protected] 8.95043215679184
[email protected] 10.3673780029897
[email protected] 14.7045336161553
[email protected] 14.739228326402
[email protected] 15.7675750942749
[email protected] 15.900579229109
[email protected] 17.5110124877347
[email protected] 17.5870177434607
[email protected] 18.8395289304497
[email protected] 23.098494164021
[email protected] 24.1675876782456
[email protected] 24.9660377482334
[email protected] 25.5276956420347
[email protected] 25.7255831708127
[email protected] 25.7681376971986
[email protected] 28.0332800246033
[email protected] 28.4146869550709
[email protected] 29.7972595531369
[email protected] 30.2951171907619
[email protected] 30.6888962524812

1-50

36 Brahui 8.950432157
24 Balochi 10.367378
87 Kalash 14.70453362
176 Tajik_Pomiri 14.73922833
145 Pathan 15.76757509
175 Tadjik 15.90057923
5 Afghan_Uzbeki 17.51101249
3 Afghan_Tadjik 17.58701774
39 Burusho 18.83952893
107 Lezgin 23.09849416
43 Chechen 24.16758768
97 Kumyk 24.96603775
2 Adygei 25.52769564
138 North_Ossetian 25.72558317
23 Balkar 25.7681377
81 Iranian 28.03328002
184 Turkmen 28.41468696
1 Abkhasian 29.79725955
72 GujaratiA 30.29511719
136 Nogay 30.68889625
98 Kurdish 30.78149308
135 Nogai 30.93573545
69 Georgian 32.41245657
4 Afghan_Turkmen 32.45587189
194 Uzbek 33.54441186
195 Uzbeki 35.10498869
182 Turkish 36.53745323
73 GujaratiB 37.52222491
11 Armenian 39.27628769
83 Iranian_Jewish 40.00776265
35 Brahmin_UP 40.38506271
206 Turk Trabzon 41.41443219
34 Brahmin_TN 41.75290921
96 Kshatriya 42.46370128
13 Assyrian 43.19728118
82 Iranian_Jew 43.49993364
193 Uygur 44.48979806
74 GujaratiC 46.3371504
200 Yamnaya 46.38973531
85 Iraqi_Jewish 46.58817987
84 Iraqi_Jew 47.08110491
174 Syrian 47.28108126
106 Lebanese_Muslim 48.33970816
104 Lebanese 49.24367819
111 MA1 50.21783897
196 Velamas 50.69510731
86 Jordanian 51.18767524
46 Corded_Ware_LN 51.25034242
37 Bulgarian 51.5812446

It's interesting you come off as baloochi/Brahui. I think your central-asian affinity is really not giving you a good fit.

[Arbogan]

Also something interesting this ANE-shifted farmer component seem to have replaced whatever the earlier neolithic farmers were. That's the interesting ENF that headed into europe, became WHG shifted, ENFs that went into the caucasus and further east mixed with ANE. And ENFs that became desert pastoralists, mixed with a SSA element.

[jesus]

My Oracle

[email protected] 8,43268385594353
[email protected] 13,2604756689025
[email protected] 17,5192651830635
[email protected] 18,6040903655862
[email protected] 19,0511306744877
[email protected] 20,135597329372
[email protected] 20,5892448196336
8-Turk [email protected] 20,9320123059436
[email protected] 21,3699514552934
[email protected] 22,1571794152415
[email protected] 22,5094941894725
[email protected] 22,6343726476346
[email protected] 22,8494878137112
[email protected] 23,1221335470295
[email protected] 23,1418699612705
[email protected] 23,2423757421424
[email protected] 23,2656850549559
[email protected] 23,3052396396533
[email protected] 23,733897887208
[email protected] 24,329412672348

[surbakhunWeesste]

It's interesting you come off as baloochi/Brahui. I think your central-asian affinity is really not giving you a good fit.

Yeah! The Baloch and Brahui have ~50% and ~49% Central Asian and I am @~53. There is no Afghan Pashtun sample!

[MonkeyDLuffy]

Punjabi Ramgarhia/turkhan

Oceanian. 0.002502
European 0.104663
EEF 0.025296
East_Asian 1E-005
South_Asian 0.446122
Central_Asian 0.398439
Amerindian 0.014793
Siberian 0.008164
Sub-Saharan. 1E-005

[randwulf]

My K9 Results

Oceanian 0.00001
EEF 0.366146
European 0.467444
Amerindian 0.000780
Central_Asian 0.142732
South_Asian 0.006802
East_Asian 0.00001
Siberian 0.012159
Sub-Saharan 0.003918

[email protected] 2.19546453572516
[email protected] 6.58378042692798
[email protected] 7.08121018669833
[email protected] 7.2426308856934
[email protected] 8.08270498711601
[email protected] 8.52864477338722
[email protected] 9.65635434887193
[email protected] 9.75524296341747
[email protected] 10.1683327863704
[email protected] 10.7890925165873
[email protected] 10.8304101258309
[email protected] 11.8876936278658
[email protected] 12.7750303054866
[email protected] 13.4461366810968
[email protected] 13.7018559714588
[email protected] 13.7462413878823
[email protected] 14.7595677313354
[email protected] 14.979752206562
[email protected] 15.0931636490035
[email protected] 15.1789480509494

K6 Results:

Yamnaya_related 0.338062
WHG_extra 0.042703
ENA .007404
Middle_Eastern 0.121365
Pre-Yamnaya 0.481683
Sub-Saharan 0.008783

[Dr_McNinja]

I copied-pasted that list of populations into the 4-Ancestors Oracle program.

No alterations to the list.

HRP0393 Haryana Jatt


Least-squares method.

Using 1 population approximation:
1 GujaratiA @ 7.391495
2 Burusho @ 11.187614
3 Pathan @ 11.311578
4 GujaratiB @ 15.366359
5 Brahmin_UP @ 16.737011
6 Kshatriya @ 19.606759
7 Kalash @ 20.795937
8 Brahmin_TN @ 20.816573
9 Balochi @ 22.039537
10 Brahui @ 24.269237
11 GujaratiC @ 24.412021
12 Tajik_Pomiri @ 25.469609
13 Afghan_Tadjik @ 28.477889
14 Afghan_Uzbeki @ 28.96386
15 Tadjik @ 29.516486
16 Muslim_India @ 29.700458
17 Punjabi @ 29.770559
18 GujaratiD @ 30.748388
19 Velamas @ 30.870195
20 Dharkar @ 31.551434
206 iterations.

Using 2 populations approximation:
1 GujaratiC+Tajik_Pomiri @ 3.951898
2 Kshatriya+Tajik_Pomiri @ 4.70201
3 Punjabi+Tajik_Pomiri @ 5.091792
4 GujaratiD+Tajik_Pomiri @ 5.144861
5 Muslim_India+Tajik_Pomiri @ 5.169374
6 Brahmin_UP+Tajik_Pomiri @ 5.375834
7 Dharkar+Tajik_Pomiri @ 5.392156
8 Brahmin_TN+Tajik_Pomiri @ 5.555635
9 Kanjar+Tajik_Pomiri @ 5.783431
10 Burusho+GujaratiA @ 6.029115
11 GujaratiA+Pathan @ 6.136273
12 GujaratiB+Tajik_Pomiri @ 6.240989
13 Tajik_Pomiri+Velamas @ 6.329867
14 Brahmin_UP+Pathan @ 7.065732
15 Tajik_Pomiri+Uttar_Pradesh @ 7.314072
16 Kurumba+Tajik_Pomiri @ 7.320728
17 Brahmin_UP+Kalash @ 7.382309
18 GujaratiA+GujaratiA @ 7.391495
19 GujaratiB+Pathan @ 7.749396
20 Brahmin_UP+Burusho @ 7.833661
21321 iterations.

Using 3 populations approximation:
1 50% Velamas +25% Corded_Ware_LN +25% Kalash @ 1.435431
2 50% GujaratiD +25% Balochi +25% Yamnaya @ 1.827161
3 50% GujaratiD +25% Brahui +25% Yamnaya @ 1.872054
4 50% GujaratiC +25% Pathan +25% Yamnaya @ 1.900312
5 50% Punjabi +25% Balochi +25% Yamnaya @ 2.12869
6 50% Muslim_India +25% Balochi +25% Yamnaya @ 2.211381
7 50% GujaratiC +25% Balochi +25% Yamnaya @ 2.267805
8 50% Brahmin_TN +25% GujaratiA +25% Yamnaya @ 2.284834
9 50% GujaratiD +25% Corded_Ware_LN +25% Kalash @ 2.295334
10 50% Velamas +25% Pathan +25% Yamnaya @ 2.315834
11 50% GujaratiA +25% Velamas +25% Yamnaya @ 2.343595
12 50% GujaratiD +25% Pathan +25% Yamnaya @ 2.593595
13 50% Dharkar +25% Balochi +25% Yamnaya @ 2.659165
14 50% Punjabi +25% Brahui +25% Yamnaya @ 2.684925
15 50% Muslim_India +25% Brahui +25% Yamnaya @ 2.769444
16 50% Punjabi +25% Kalash +25% Yamnaya @ 2.838419
17 50% Dharkar +25% Brahui +25% Yamnaya @ 2.892587
18 50% GujaratiB +25% Brahmin_TN +25% Yamnaya @ 2.894226
19 50% Velamas +25% Tajik_Pomiri +25% Yamnaya @ 2.938063
20 50% GujaratiA +25% Brahmin_UP +25% Tajik_Pomiri @ 2.939034
1534976 iterations.

Using 4 populations approximation:
1 Brahmin_TN+Pathan+Velamas+Yamnaya @ 0.915859
2 GujaratiC+Pathan+Velamas+Yamnaya @ 0.979796
3 Brahmin_TN+GujaratiD+Pathan+Yamnaya @ 1.068029
4 Balochi+GujaratiC+Kanjar+Yamnaya @ 1.139179
5 Kshatriya+Pathan+Velamas+Yamnaya @ 1.209756
6 Balochi+Dharkar+GujaratiC+Yamnaya @ 1.223638
7 Balochi+GujaratiB+Kol+Yamnaya @ 1.28272
8 Balochi+GujaratiC+GujaratiD+Yamnaya @ 1.314669
9 Balochi+Kshatriya+Kurumba+Yamnaya @ 1.316118
10 Balochi+Brahmin_TN+Kanjar+Yamnaya @ 1.329226
11 Balochi+GujaratiB+Piramalai+Yamnaya @ 1.352113
12 Balochi+GujaratiC+Punjabi+Yamnaya @ 1.411509
13 Brahmin_TN+Kurumba+Pathan+Yamnaya @ 1.431652
14 Corded_Ware_LN+Kalash+Velamas+Velamas @ 1.435431
15 Balochi+GujaratiC+Muslim_India+Yamnaya @ 1.444523
16 Balochi+Brahmin_TN+Kol+Yamnaya @ 1.454144
17 GujaratiB+Kurumba+Pathan+Yamnaya @ 1.459573
18 Balochi+Brahmin_TN+Uttar_Pradesh+Yamnaya @ 1.470462
19 Balochi+Brahmin_UP+Piramalai+Yamnaya @ 1.575504
20 Balochi+Brahmin_UP+Kurumba+Yamnaya @ 1.581436
21 Balochi+Chamar+GujaratiB+Yamnaya @ 1.589512
22 Corded_Ware_LN+GujaratiD+Kalash+Velamas @ 1.596584
23 Balochi+GujaratiD+Punjabi+Yamnaya @ 1.599198
24 Balochi+GujaratiD+Muslim_India+Yamnaya @ 1.604058
25 GujaratiC+GujaratiD+Pathan+Yamnaya @ 1.629904
26 Balochi+GujaratiC+Kurumba+Yamnaya @ 1.640802
27 Balochi+GujaratiC+Uttar_Pradesh+Yamnaya @ 1.648052
28 Balochi+Kol+Kshatriya+Yamnaya @ 1.677548
29 Balochi+Kshatriya+Piramalai+Yamnaya @ 1.701321
30 Balochi+GujaratiB+Sakilli+Yamnaya @ 1.724539
31 Balochi+Dusadh+GujaratiB+Yamnaya @ 1.783626
32 Balochi+Kshatriya+Uttar_Pradesh+Yamnaya @ 1.794533
33 Balochi+Kanjar+Kshatriya+Yamnaya @ 1.80583
34 Balochi+Brahmin_TN+Dharkar+Yamnaya @ 1.809786
35 Balochi+GujaratiB+Uttar_Pradesh+Yamnaya @ 1.819573
36 Balochi+GujaratiD+GujaratiD+Yamnaya @ 1.827161
37 Balochi+Dharkar+GujaratiD+Yamnaya @ 1.834231
38 Balochi+Brahmin_UP+Kol+Yamnaya @ 1.84331
39 Balochi+Brahmin_TN+Dusadh+Yamnaya @ 1.848665
40 Brahui+GujaratiC+Kanjar+Yamnaya @ 1.851408
2882475 iterations.


Gaussian method.
Noise dispersion set to 0.584552

Using 1 population approximation:
1 GujaratiA @ 3.269541
2 Pathan @ 6.125443
3 Brahmin_UP @ 6.495126
4 GujaratiB @ 6.596802
5 Kshatriya @ 8.08091
6 Burusho @ 8.236974
7 Kalash @ 9.893941
8 Brahmin_TN @ 10.439813
9 GujaratiC @ 10.66104
10 Balochi @ 11.453757
11 Tajik_Pomiri @ 12.139869
12 Brahui @ 12.464226
13 Punjabi @ 12.760885
14 Muslim_India @ 13.014674
15 Dharkar @ 13.168665
16 Kanjar @ 13.78717
17 Afghan_Tadjik @ 14.322651
18 Afghan_Uzbeki @ 14.411198
19 Tadjik @ 15.032895
20 GujaratiD @ 16.090707
206 iterations.

Using 2 populations approximation:
1 GujaratiA+GujaratiA @ 3.269541
2 GujaratiA+Kalash @ 4.179245
3 GujaratiA+Pathan @ 4.269255
4 Brahmin_UP+Kalash @ 4.370185
5 Brahmin_UP+Pathan @ 4.66881
6 Brahmin_UP+GujaratiA @ 4.840281
7 GujaratiA+GujaratiB @ 4.845414
8 GujaratiC+Tajik_Pomiri @ 4.929669
9 GujaratiB+Pathan @ 4.937672
10 GujaratiD+Tajik_Pomiri @ 5.118716
11 Kanjar+Tajik_Pomiri @ 5.148373
12 GujaratiB+Tajik_Pomiri @ 5.184175
13 Brahmin_UP+Tajik_Pomiri @ 5.195055
14 Kalash+Kshatriya @ 5.220952
15 GujaratiB+Kalash @ 5.225459
16 Kshatriya+Tajik_Pomiri @ 5.240173
17 Kshatriya+Pathan @ 5.398375
18 Dharkar+Tajik_Pomiri @ 5.428175
19 Tajik_Pomiri+Velamas @ 5.470505
20 Brahmin_TN+Tajik_Pomiri @ 5.486743
21321 iterations.

Using 3 populations approximation:
1 50% GujaratiA +25% Velamas +25% Yamnaya @ 2.369969
2 50% GujaratiA +25% GujaratiD +25% Yamnaya @ 2.673017
3 50% Velamas +25% Pathan +25% Yamnaya @ 2.747245
4 50% GujaratiA +25% GujaratiC +25% Yamnaya @ 2.764551
5 50% GujaratiC +25% Pathan +25% Yamnaya @ 2.831464
6 50% GujaratiD +25% Corded_Ware_LN +25% Kalash @ 2.872224
7 50% GujaratiD +25% Pathan +25% Yamnaya @ 2.87511
8 50% Velamas +25% Corded_Ware_LN +25% Kalash @ 2.883114
9 50% GujaratiA +25% GujaratiA +25% Kalash @ 2.984515
10 50% GujaratiC +25% Corded_Ware_LN +25% Kalash @ 3.060334
11 50% GujaratiB +25% GujaratiA +25% Yamnaya @ 3.068078
12 50% GujaratiA +25% Kanjar +25% Yamnaya @ 3.118382
13 50% GujaratiA +25% GujaratiB +25% Yamnaya @ 3.119453
14 50% GujaratiA +25% Brahmin_TN +25% Yamnaya @ 3.134186
15 50% GujaratiC +25% GujaratiA +25% Yamnaya @ 3.174994
16 50% GujaratiD +25% Balochi +25% Yamnaya @ 3.185299
17 50% GujaratiA +25% Corded_Ware_LN +25% Velamas @ 3.221288
18 50% GujaratiA +25% Brahmin_UP +25% Yamnaya @ 3.231492
19 50% GujaratiC +25% Balochi +25% Yamnaya @ 3.235116
20 50% Velamas +25% GujaratiA +25% Yamnaya @ 3.241351
3514256 iterations.

Using 4 populations approximation:
1 GujaratiA+GujaratiA+Velamas+Yamnaya @ 2.369969
2 GujaratiA+GujaratiA+GujaratiD+Yamnaya @ 2.673017
3 GujaratiC+Pathan+Velamas+Yamnaya @ 2.678615
4 Pathan+Velamas+Velamas+Yamnaya @ 2.747245
5 GujaratiA+GujaratiA+GujaratiC+Yamnaya @ 2.764551
6 GujaratiD+Pathan+Velamas+Yamnaya @ 2.76779
7 GujaratiA+GujaratiB+Velamas+Yamnaya @ 2.767964
8 GujaratiC+GujaratiD+Pathan+Yamnaya @ 2.788836
9 GujaratiB+Pathan+Velamas+Yamnaya @ 2.798
10 Corded_Ware_LN+GujaratiD+Kalash+Velamas @ 2.823948
11 GujaratiC+GujaratiC+Pathan+Yamnaya @ 2.831464
12 Brahmin_UP+GujaratiA+Velamas+Yamnaya @ 2.844593
13 Corded_Ware_LN+GujaratiC+Kalash+Velamas @ 2.851242
14 Corded_Ware_LN+GujaratiD+GujaratiD+Kalash @ 2.872224
15 GujaratiD+GujaratiD+Pathan+Yamnaya @ 2.87511
16 Corded_Ware_LN+Kalash+Velamas+Velamas @ 2.883114
17 Brahmin_UP+Pathan+Velamas+Yamnaya @ 2.885497
18 GujaratiB+GujaratiD+Pathan+Yamnaya @ 2.891841
19 Corded_Ware_LN+GujaratiC+GujaratiD+Kalash @ 2.906746
20 Kshatriya+Pathan+Velamas+Yamnaya @ 2.980623
21 GujaratiA+GujaratiA+GujaratiA+Kalash @ 2.984515
22 GujaratiA+GujaratiB+GujaratiC+Yamnaya @ 2.997706
23 Kanjar+Pathan+Velamas+Yamnaya @ 3.007042
24 Brahmin_UP+GujaratiD+Pathan+Yamnaya @ 3.023509
25 Brahmin_TN+Pathan+Velamas+Yamnaya @ 3.024521
26 Brahmin_TN+GujaratiA+Velamas+Yamnaya @ 3.041018
27 GujaratiA+Pathan+Velamas+Yamnaya @ 3.047972
28 Corded_Ware_LN+Kalash+Kanjar+Velamas @ 3.05098
29 Corded_Ware_LN+GujaratiC+GujaratiC+Kalash @ 3.060334
30 GujaratiA+GujaratiB+GujaratiB+Yamnaya @ 3.068078
31 GujaratiA+Kshatriya+Velamas+Yamnaya @ 3.079878
32 Brahmin_TN+GujaratiD+Pathan+Yamnaya @ 3.100642
33 Brahmin_UP+GujaratiA+GujaratiC+Yamnaya @ 3.101839
34 GujaratiA+GujaratiC+Velamas+Yamnaya @ 3.108535
35 GujaratiB+GujaratiC+Pathan+Yamnaya @ 3.109583
36 GujaratiA+GujaratiD+Pathan+Yamnaya @ 3.109719
37 Corded_Ware_LN+GujaratiB+Kalash+Velamas @ 3.115644
38 GujaratiA+GujaratiB+GujaratiD+Yamnaya @ 3.115875
39 GujaratiA+GujaratiA+Kanjar+Yamnaya @ 3.118382
40 GujaratiD+Kshatriya+Pathan+Yamnaya @ 3.118779
39600817 iterations.

Similar pattern mentioned in ancient South Asian DNA thread. Where there's Balochi, then there's two Indian populations and Yamnaya. In my run I had mostly Indian populations but whenever Balochi was in there, it would be met with two Indian pops and Tajik_Pomiri. Otherwise it'd be three Indian pops and Lezgin/Chechen.

[parasar]

Punjabi Ramgarhia/turkhan

Oceanian. 0.002502
European 0.104663
EEF 0.025296
East_Asian 1E-005
South_Asian 0.446122
Central_Asian 0.398439
Amerindian 0.014793
Siberian 0.008164
Sub-Saharan. 1E-005

You may already know this but there was a tarkhan dynasty in Sindh.

Tarkhans were of the artisan (blacksmith/carpenter) class.
“a blacksmith, a handcraftsman" 'a privileged person who is exempt from all government taxes'.
"Tarqan in Ancient Turkic was considered to be the supreme title ... used as adjective meaning 'sacred, celebrated'."
"Indo(Panjabi) tarkhan, Kurd. terxan, Armen. t'arxan,
Grek. ταρχανος, Tibet. t'ar-k'an, Rus. tarchan"
http://altaica.ru/LIBRARY/CHOI/choi2000.pdf

[Anglecynn]

Papuan 0.00001
EEF 0.325419
European 0.501587
Amerindian 0.008591
Central_Asian 0.155785
South_Asian 0.002904
East_Asian 0.00001
Siberian 0.001819
Sub-Saharan 0.003875

-----------------------
European: 50.15%
EEF: 32.54%
Central Asian: 15.57%

Amerindian: 0.85%
Sub-Saharan: 0.38%
South Asian: 0.29%
Siberian: 0.18%

Papuan: 0%
East Asian: 0%

Those are mine, anyone kind enough to run the oracle for me? :D

Makes sense judging by the results of others here, and i guess my EEF or Central Asian (or both?) are slightly above average for my population as normal.

[Arbogan]

Looks like: European-blue is WHG/hunter gatherer predominant. Central asian: ANE shifted and EEF :ENF and EEF composite of all the ENF and EEF signals.

[MonkeyDLuffy]

You may already know this but there was a tarkhan dynasty in Sindh.

Tarkhans were of the artisan (blacksmith/carpenter) class.
“a blacksmith, a handcraftsman" 'a privileged person who is exempt from all government taxes'.
"Tarqan in Ancient Turkic was considered to be the supreme title ... used as adjective meaning 'sacred, celebrated'."
"Indo(Panjabi) tarkhan, Kurd. terxan, Armen. t'arxan,
Grek. ταρχανος, Tibet. t'ar-k'an, Rus. tarchan"
http://altaica.ru/LIBRARY/CHOI/choi2000.pdf

Woah, thanks! I had no idea. I always thought we were just normal carpenter tribe, because there is no big historical data on us! Ramgarhia is just a title used by Sikh tarkhans.

[Jessie]

Mine

Oceanian 0.00001
EEF 0.294425
European 0.520847
Amerindian 0.005177
Central_Asian 0.165499
South_Asian 0.014013
East_Asian 0.00001
Siberian 0.00001
Sub-Saharan 0.00001

My mother's
Oceanian 0.00001
EEF 0.289851
European 0.516483
Amerindian 0.010232
Central_Asian 0.178387
South_Asian 0.005007
East_Asian 0.00001
Siberian 0.00001
Sub-Saharan 0.00001

If someone could kindly do an Oracle I would be interested in where we plot. I was with the West Scots with the K8 and my mother was Ukraine-Kiev.

There doesn't appear to be a thread for the K6 so I'll list here.

Mine

Yamnaya_related 0.424978
WHG_extra 0.025084
ENA 0.008418
Middle_Eastern 0.048719
Pre-Yamnaya 0.492791
Sub-Saharan 0.00001

Mother

Yamnaya_related 0.40708
WHG_extra 0.032474
ENA 0.009364
Middle_Eastern 0.057797
Pre-Yamnaya 0.493475
Sub-Saharan 0.00001

[The Barnacle]

Thanks to Anabasis and noel.

[email protected] 9,9605622231033
[email protected] 11,4590933274263
[email protected] 11,5598934194944
[email protected] 12,3462077343359
[email protected] 14,1807596436462
[email protected] 14,2139369181811
[email protected] 14,5633631943741
[email protected] 16,8591025494479
[email protected] 16,9481614291816
[email protected] 25,3838172278718
[email protected] 25,7585169723348
[email protected] 26,4091771448807
[email protected] 27,22172826594
[email protected] 28,3123217946516
[email protected] 28,5569527972498
[email protected] 28,7272467646322
[email protected] 28,7464458693314
[email protected] 30,6231591907534
[email protected] 31,0577607811856
[email protected] 31,1952668579251

Rukha how the hell are you closer to a Gujarati than an Iranian? Sometimes I actually think these are just not real at all

[The Barnacle]

pretty interesting

[email protected] 8.95043215679184
[email protected] 10.3673780029897
[email protected] 14.7045336161553
[email protected] 14.739228326402
[email protected] 15.7675750942749
[email protected] 15.900579229109
[email protected] 17.5110124877347
[email protected] 17.5870177434607
[email protected] 18.8395289304497
[email protected] 23.098494164021
[email protected] 24.1675876782456
[email protected] 24.9660377482334
[email protected] 25.5276956420347
[email protected] 25.7255831708127
[email protected] 25.7681376971986
[email protected] 28.0332800246033
[email protected] 28.4146869550709
[email protected] 29.7972595531369
[email protected] 30.2951171907619
[email protected] 30.6888962524812

1-50

36 Brahui 8.950432157
24 Balochi 10.367378
87 Kalash 14.70453362
176 Tajik_Pomiri 14.73922833
145 Pathan 15.76757509
175 Tadjik 15.90057923
5 Afghan_Uzbeki 17.51101249
3 Afghan_Tadjik 17.58701774
39 Burusho 18.83952893
107 Lezgin 23.09849416
43 Chechen 24.16758768
97 Kumyk 24.96603775
2 Adygei 25.52769564
138 North_Ossetian 25.72558317
23 Balkar 25.7681377
81 Iranian 28.03328002
184 Turkmen 28.41468696
1 Abkhasian 29.79725955
72 GujaratiA 30.29511719
136 Nogay 30.68889625
98 Kurdish 30.78149308
135 Nogai 30.93573545
69 Georgian 32.41245657
4 Afghan_Turkmen 32.45587189
194 Uzbek 33.54441186
195 Uzbeki 35.10498869
182 Turkish 36.53745323
73 GujaratiB 37.52222491
11 Armenian 39.27628769
83 Iranian_Jewish 40.00776265
35 Brahmin_UP 40.38506271
206 Turk Trabzon 41.41443219
34 Brahmin_TN 41.75290921
96 Kshatriya 42.46370128
13 Assyrian 43.19728118
82 Iranian_Jew 43.49993364
193 Uygur 44.48979806
74 GujaratiC 46.3371504
200 Yamnaya 46.38973531
85 Iraqi_Jewish 46.58817987
84 Iraqi_Jew 47.08110491
174 Syrian 47.28108126
106 Lebanese_Muslim 48.33970816
104 Lebanese 49.24367819
111 MA1 50.21783897
196 Velamas 50.69510731
86 Jordanian 51.18767524
46 Corded_Ware_LN 51.25034242
37 Bulgarian 51.5812446


This doesn't actually represent FST distances between populations genetically right? I'm baffled as to why we are closer to Caucasians than our neighbours ( Iran) according to this oracle. I'm one confused guy here.

[Radboud]

Mine

Oceanian 0.00001
EEF 0.294425
European 0.520847
Amerindian 0.005177
Central_Asian 0.165499
South_Asian 0.014013
East_Asian 0.00001
Siberian 0.00001
Sub-Saharan 0.00001

My mother's
Oceanian 0.00001
EEF 0.289851
European 0.516483
Amerindian 0.010232
Central_Asian 0.178387
South_Asian 0.005007
East_Asian 0.00001
Siberian 0.00001
Sub-Saharan 0.00001

If someone could kindly do an Oracle I would be interested in where we plot. I was with the West Scots with the K8 and my mother was Ukraine-Kiev.

Jessie, you and your mother are quite similar to some NL/Dutch samples according to this spreadsheet.

https://docs.google.com/spreadsheets/d/1_QDeZe1DKNHizRbFRFODVfxvxW0mYnRFJxwOOewFAHA/edit#gid=1930392688

[Helgenes50]

Mine

Oceanian 0.00001
EEF 0.294425
European 0.520847
Amerindian 0.005177
Central_Asian 0.165499
South_Asian 0.014013
East_Asian 0.00001
Siberian 0.00001
Sub-Saharan 0.00001

My mother's
Oceanian 0.00001
EEF 0.289851
European 0.516483
Amerindian 0.010232
Central_Asian 0.178387
South_Asian 0.005007
East_Asian 0.00001
Siberian 0.00001
Sub-Saharan 0.00001

If someone could kindly do an Oracle I would be interested in where we plot. I was with the West Scots with the K8 and my mother was Ukraine-Kiev.

There doesn't appear to be a thread for the K6 so I'll list here.

Mine

Yamnaya_related 0.424978
WHG_extra 0.025084
ENA 0.008418
Middle_Eastern 0.048719
Pre-Yamnaya 0.492791
Sub-Saharan 0.00001

Mother

Yamnaya_related 0.40708
WHG_extra 0.032474
ENA 0.009364
Middle_Eastern 0.057797
Pre-Yamnaya 0.493475
Sub-Saharan 0.00001

Your results are very interesting.
Your Central_Asian is lower than your mother but your Yamnaya_related is higher

I would have thought the opposite

[Kurd]

According to the K9 spreadsheet, my Central Asian & S Asian is around the Tajik average. Since there appears to be a good reference K9 spreadsheet (many Asians), I will be doing an Anthrogenica community PCA & graphs incorporating some of the references this weekend hopefully. I may post the charts and graphs under a new thread.

http://i.imgur.com/tgufZhJ.jpg
http://i.imgur.com/xQmN5mq.jpg

[Jessie]

Your results are very interesting.
Your Central_Asian is lower than your mother but your Yamnaya_related is higher

I would have thought the opposite

I double checked again and those are the results. It is difficult to compare as not many have posted their Yamnaya results. The other thing I noticed was my mother has nearly twice the amount of Amerindian as myself.

[Arbogan]

Your results are very interesting.
Your Central_Asian is lower than your mother but your Yamnaya_related is higher

I would have thought the opposite

Different SNPs. Also k6 probably doesnt correlate highly with k9 entirely. Also k9 seems a little noisier than k6 and k8.

[Arbogan]

According to the K9 spreadsheet, my Central Asian & S Asian is around the Tajik average. Since there appears to be a good reference K9 spreadsheet (many Asians), I will be doing an Anthrogenica community PCA & graphs incorporating some of the references this weekend hopefully. I may post the charts and graphs under a new thread.

http://i.imgur.com/tgufZhJ.jpg
http://i.imgur.com/xQmN5mq.jpg
largely consistent with other admixture tests(although this test doubles your south-asian affinity).Im making a spreadsheet for west iranic members. Do you mind if i list your results?


Rukha how the hell are you closer to a Gujarati than an Iranian? Sometimes I actually think these are just not real at all The looks at total affinity and depending on total affinity rather than relatedness you can look more similar to a gujarati proportionally.

[Helgenes50]

I double checked again and those are the results. It is difficult to compare as not many have posted their Yamnaya results. The other thing I noticed was my mother has nearly twice the amount of Amerindian as myself.

It would be interesting to compare the K6 and K9 results.
But that makes sense, some of us are more EHG or more Central Asian
via the Yamnaya Ancestry.

My Amerindian is of 0.8 % between you and your mother

My K9 results


European 48.77 %
EEF 36.08 %
Central_Asian 13.94 %
Amerindian 0.8 %
Sub-Saharan 0.37 %
Oceanian 0%
East_Asian 0%
South_Asian 0%
Siberian 0 %

Now my K6

Yamnaya_related 37.34
WHG_extra 0.256
ENA 0.00001
Middle_Eastern 0.421
Pre-Yamnaya 54.94
Sub-Saharan 0.92

[Helgenes50]

Different SNPs. Also k6 probably doesnt correlate highly with k9 entirely. Also k9 seems a little noisier than k6 and k8.

I was wondering which one was the most accurate K6 or K9

[Kurd]

largely consistent with other admixture tests(although this test doubles your south-asian affinity).Im making a spreadsheet for west iranic members. Do you mind if i list your results?



Sure, no problem

[Anabasis]

All in One

Yamnaya K6

Yamnaya_related 0.039816
WHG_extra 0.017804
ENA 0.00001
Middle_Eastern 0.771227
Pre-Yamnaya 0.171133
Sub-Saharan 0.00001

K9 Results

Oceanian 0,00001
EEF 0,458997
European 0,00001
Amerindian 0,00001
Central_Asian 0,540933
South_Asian 0,00001
East_Asian 0,00001
Siberian 0,00001
Sub-Saharan 0,00001

K8 Results
ANE 0.151945
South_Eurasian 0.013973
Near_Eastern 0.815005
East_Eurasian 1E-005
WHG 0.015921
Oceanian 1E-005
Pygmy 0.003126
Sub-Saharan 1E-005

[The Barnacle]

largely consistent with other admixture tests(although this test doubles your south-asian affinity).Im making a spreadsheet for west iranic members. Do you mind if i list your results?

The looks at total affinity and depending on total affinity rather than relatedness you can look more similar to a gujarati proportionally.

So which calculator if Any shows relatedness etc?

[Kurd]

According to the K9 spreadsheet, my Central Asian & S Asian is around the Tajik average. Since there appears to be a good reference K9 spreadsheet (many Asians), I will be doing an Anthrogenica community PCA & graphs incorporating some of the references this weekend hopefully. I may post the charts and graphs under a new thread.

http://i.imgur.com/tgufZhJ.jpg
http://i.imgur.com/xQmN5mq.jpg

K9 Oracle, courtesy Anabasis:

http://i.imgur.com/8i9aZ2K.jpg

[Dr_McNinja]

This doesn't actually represent FST distances between populations genetically right? I'm baffled as to why we are closer to Caucasians than our neighbours ( Iran) according to this oracle. I'm one confused guy here.GujaratiA has 37.49% Central Asian, 11.85% European, 45.61% South Asian, 3.15 EEF. It's the most West-leaning Indian population in the spreadsheet. The genetic distance is great in all the one population matches but there's at least half "overlap" there in terms of Central Asian/European.

Also, Iranians have a lot of Middle Eastern admixture along with ancient Caucasus ancestry (or perhaps the Caucasus has Iranian ancestry depending on how you view it).

Afghans likely have admixture direct from the Caucasus recently in addition to Indo-European Steppe ancestry in common with the North Caucasus populations (high ANE in both). The Near Eastern admixture is very small compared to Iranians. So they'll show up more similar to Caucasians, like Caucasus mixed with South Asia, whereas Iranians are modeled as Caucasus mixed with Middle East.

Relatedness to modern day Iranians would be shown better through IBD analysis.

[MonkeyDLuffy]

Can someone please make oracle of my results too? Thanks

[Arbogan]

GujaratiA has 37.49% Central Asian, 11.85% European, 45.61% South Asian, 3.15 EEF. It's the most West-leaning Indian population in the spreadsheet. The genetic distance is great in all the one population matches but there's at least half "overlap" there in terms of Central Asian/European.

Also, Iranians have a lot of Middle Eastern admixture along with ancient Caucasus ancestry (or perhaps the Caucasus has Iranian ancestry depending on how you view it).

Afghans likely have admixture direct from the Caucasus recently in addition to Indo-European Steppe ancestry in common with the North Caucasus populations (high ANE in both). The Near Eastern admixture is very small compared to Iranians. So they'll show up more similar to Caucasians, like Caucasus mixed with South Asia, whereas Iranians are modeled as Caucasus mixed with Middle East.

Relatedness to modern day Iranians would be shown better through IBD analysis.

More likely that caucasians and afghans share zagros neolithic ancestry with west iranics. Considering the oldest neolithic sites are 8000 b.c in the zagros range. Kermanshah and loorestan have some of the first sites. And gedrosia/west-asian in the zagros peaks in the South-west. There are even paleolithic age neanderthals and homo sapiens in the zagros.

[parasar]

Rukha how the hell are you closer to a Gujarati than an Iranian? Sometimes I actually think these are just not real at all

The samples must be from western parts of Iran. Western parts of Iran are more akin to middle-easterners.
If the samples had been from Zabol, Sistan-Baluchistan, I think the affinity would be reversed.

[SwampThing27]

Papuan 0.00001
EEF 0.325419
European 0.501587
Amerindian 0.008591
Central_Asian 0.155785
South_Asian 0.002904
East_Asian 0.00001
Siberian 0.001819
Sub-Saharan 0.003875

-----------------------
European: 50.15%
EEF: 32.54%
Central Asian: 15.57%

Amerindian: 0.85%
Sub-Saharan: 0.38%
South Asian: 0.29%
Siberian: 0.18%

Papuan: 0%
East Asian: 0%

Those are mine, anyone kind enough to run the oracle for me? :D

Makes sense judging by the results of others here, and i guess my EEF or Central Asian (or both?) are slightly above average for my population as normal.

Here is your oracle. Very similar to mine a few pages back, but you're a closer fit to the English:

[email protected] 1.73894977736565
[email protected] 4.68056566713629
[email protected] 5.48946456746922
[email protected] 5.81497973957777
[email protected] 6.3781036288226
[email protected] 7.25533586821382
[email protected] 7.3504793956653
[email protected] 7.6656776099703
[email protected] 7.67678980254117
[email protected] 7.94790349075798
[email protected] 8.53211261093201
[email protected] 9.48739097223257
[email protected] 9.53965697620436
[email protected] 10.0561991090869
[email protected] 10.9646560696935
[email protected] 11.7944722764522
[email protected] 12.1559078807511
[email protected] 12.3482956143603
[email protected] 13.2051431510636
[email protected] 13.7120162646822

[SwampThing27]

Mine

Oceanian 0.00001
EEF 0.294425
European 0.520847
Amerindian 0.005177
Central_Asian 0.165499
South_Asian 0.014013
East_Asian 0.00001
Siberian 0.00001
Sub-Saharan 0.00001

My mother's
Oceanian 0.00001
EEF 0.289851
European 0.516483
Amerindian 0.010232
Central_Asian 0.178387
South_Asian 0.005007
East_Asian 0.00001
Siberian 0.00001
Sub-Saharan 0.00001

If someone could kindly do an Oracle I would be interested in where we plot. I was with the West Scots with the K8 and my mother was Ukraine-Kiev.

There doesn't appear to be a thread for the K6 so I'll list here.

Mine

Yamnaya_related 0.424978
WHG_extra 0.025084
ENA 0.008418
Middle_Eastern 0.048719
Pre-Yamnaya 0.492791
Sub-Saharan 0.00001

Mother

Yamnaya_related 0.40708
WHG_extra 0.032474
ENA 0.009364
Middle_Eastern 0.057797
Pre-Yamnaya 0.493475
Sub-Saharan 0.00001

Jessie:
[email protected] 1.29241992184236
[email protected] 2.55853082103772
[email protected] 2.74002433383355
[email protected] 3.26116144030007
[email protected] 3.72002457197531
[email protected] 4.30946756321507
[email protected] 5.8790977564589
[email protected] 6.14067358637268
[email protected] 6.85376880990306
[email protected] 7.69032964291302
[email protected] 8.22799724781189
[email protected] 9.12976115475991
[email protected] 9.51552154530552
[email protected] 9.75539461049116
[email protected] 10.1709212287101
[email protected] 10.5559394830588
[email protected] 10.5871421571688
[email protected] 10.7906364443891
[email protected] 10.9863855184259
[email protected] 12.7442547104489

Jessie's Mom:
[email protected] 1.46676100622255
[email protected] 1.78060487467041
[email protected] 2.35526959391064
[email protected] 3.09226442695316
[email protected] 3.84342146402135
[email protected] 4.31952646556728
[email protected] 5.2575871226733
[email protected] 5.69539134051384
[email protected] 6.0013524858985
[email protected] 6.62376213441677
[email protected] 7.45154292881682
[email protected] 8.02722973617969
[email protected] 8.90515413485568
[email protected] 9.13627673718348
[email protected] 9.40329103535698
[email protected] 9.93559626656096
[email protected] 10.002058332279
[email protected] 11.4127959166308
[email protected] 11.6554173395893
[email protected] 11.9314257593466

[Radboud]

Swampthing27, can you do mine please?:)



Oceanian European EEF East_Asian South_Asian Central_Asian Amerindian Siberian Sub-Saharan
0.004416 0.516085 0.288243 1.00E-05 1.00E-05 0.190616 1.00E-05 0.0006 1.00E-05

[SwampThing27]

Can someone please make oracle of my results too? Thanks

Here are yours:

[email protected] 3.00851949303972
[email protected] 9.45112326014216
[email protected] 12.6282079286686
[email protected] 12.9746585608054
[email protected] 13.4589262792858
[email protected] 14.582251264551
[email protected] 14.7086315414814
[email protected] 18.7280706235319
[email protected] 22.0923023508048
[email protected] 22.2687029067648
[email protected] 24.3413329626789
[email protected] 24.7291774159433
[email protected] 24.7924020712748
[email protected] 24.9142098312268
[email protected] 25.108319127665
[email protected] 26.7099192074964
[email protected] 28.7273707559249
[email protected] 29.2513978538441
[email protected] 29.9924896230521
[email protected] 31.1943463667347

[Jessie]

Jessie:
[email protected] 1.29241992184236
[email protected] 2.55853082103772
[email protected] 2.74002433383355
[email protected] 3.26116144030007
[email protected] 3.72002457197531
[email protected] 4.30946756321507
[email protected] 5.8790977564589
[email protected] 6.14067358637268
[email protected] 6.85376880990306
[email protected] 7.69032964291302
[email protected] 8.22799724781189
[email protected] 9.12976115475991
[email protected] 9.51552154530552
[email protected] 9.75539461049116
[email protected] 10.1709212287101
[email protected] 10.5559394830588
[email protected] 10.5871421571688
[email protected] 10.7906364443891
[email protected] 10.9863855184259
[email protected] 12.7442547104489

Jessie's Mom:
[email protected] 1.46676100622255
[email protected] 1.78060487467041
[email protected] 2.35526959391064
[email protected] 3.09226442695316
[email protected] 3.84342146402135
[email protected] 4.31952646556728
[email protected] 5.2575871226733
[email protected] 5.69539134051384
[email protected] 6.0013524858985
[email protected] 6.62376213441677
[email protected] 7.45154292881682
[email protected] 8.02722973617969
[email protected] 8.90515413485568
[email protected] 9.13627673718348
[email protected] 9.40329103535698
[email protected] 9.93559626656096
[email protected] 10.002058332279
[email protected] 11.4127959166308
[email protected] 11.6554173395893
[email protected] 11.9314257593466

Thank you Swampthing27. This is brilliant.

[SwampThing27]

Swampthing27, can you do mine please?:)

Sure, here you go:

[email protected] 1.14098764397342
[email protected] 2.67106884025384
[email protected] 2.87781727355994
[email protected] 3.88360547509656
[email protected] 4.41551348838389
[email protected] 4.70545495162117
[email protected] 4.99215384246871
[email protected] 5.08822944388321
[email protected] 5.89029395587917
[email protected] 6.43018070352615
[email protected] 7.08552722173869
[email protected] 7.28550251265154
[email protected] 8.57501550001732
[email protected] 8.89406024301612
[email protected] 9.02994803504566
[email protected] 9.56624042579424
[email protected] 9.59188251948722
[email protected] 11.4353719540206
[email protected] 11.9335975185467
[email protected] 12.5432679593478

[SwampThing27]

K9 vs K6:

Oceanian .03606%
European 48.95%
EEF 31.8246%
East_Asian .001%
South_Asian 02.1088%
Central_Asian 15.5131%
Amerindian .02273%
Siberian .001%
Sub-Saharan 1.0581%


Yamnaya_related - 39.5%
WHG_extra - 2%
ENA - 2%
Middle_Eastern - 5.5%
Pre-Yamnaya - 50%
Sub-Saharan - 1%

Does anyone have an opinion on the ENA component for the k6? All I was able to find was ENA stands for Eastern Non-African, but not much more.

[Radboud]

Does anyone have an opinion on the ENA component for the k6? All I was able to find was ENA stands for Eastern Non-African, but not much more.

Thanks for the results!

ENA is East Asian.

[Salkin]

K9 Teal Oracle Worksheet. paste your results into INPUT area with not using (dot) but (comma) as decimal separator.

https://drive.google.com/file/d/0Bx9OviX7j0B2RUVpb05uU0xwdVU/view?usp=sharing

Interesting! That sheet put me very close (~1.7) to Bell_Beaker_LN. Next closest are Icelandic and Norwegian and they are both over 3.

[CelticGerman]

Czechs are quite high in many oracle results. In my case it's on top, whereas my Czech ancestry represents only 1.8% of my known ancestry. Unfortunately, there are no German samples. In my case Czech seems to replace (North)German. I don't know why .... Any thoughts?

[The Barnacle]

The samples must be from western parts of Iran. Western parts of Iran are more akin to middle-easterners.
If the samples had been from Zabol, Sistan-Baluchistan, I think the affinity would be reversed.

It doesn't matter because west or East Iran they should be closer to afghans. But thanks to Dr Mcninja and Baibar I understand now, this obviously doesn't show relatedness just similar proportions etc.

[The Barnacle]

GujaratiA has 37.49% Central Asian, 11.85% European, 45.61% South Asian, 3.15 EEF. It's the most West-leaning Indian population in the spreadsheet. The genetic distance is great in all the one population matches but there's at least half "overlap" there in terms of Central Asian/European.

Also, Iranians have a lot of Middle Eastern admixture along with ancient Caucasus ancestry (or perhaps the Caucasus has Iranian ancestry depending on how you view it).

Afghans likely have admixture direct from the Caucasus recently in addition to Indo-European Steppe ancestry in common with the North Caucasus populations (high ANE in both). The Near Eastern admixture is very small compared to Iranians. So they'll show up more similar to Caucasians, like Caucasus mixed with South Asia, whereas Iranians are modeled as Caucasus mixed with Middle East.

Relatedness to modern day Iranians would be shown better through IBD analysis.

Now this makes sense...I think we need to results from west and southwest afghanistan as we'll.

[Kurd]

Thanks to Anabasis and noel.

[email protected] 9,9605622231033
[email protected] 11,4590933274263
[email protected] 11,5598934194944
[email protected] 12,3462077343359
[email protected] 14,1807596436462
[email protected] 14,2139369181811
[email protected] 14,5633631943741
[email protected] 16,8591025494479
[email protected] 16,9481614291816
[email protected] 25,3838172278718
[email protected] 25,7585169723348
[email protected] 26,4091771448807
[email protected] 27,22172826594
[email protected] 28,3123217946516
[email protected] 28,5569527972498
[email protected] 28,7272467646322
[email protected] 28,7464458693314
[email protected] 30,6231591907534
[email protected] 31,0577607811856
[email protected] 31,1952668579251

I am surprised that you, me, and Zahra have a smaller distance (larger overlap) with Tajik than Afghan Tajik. One usually associates Tajik as from Tajikstan, who are more E Eurasian shifted than Afghan Tajiks. I guess it is possible that the "Tajiks" may not be Tajikstan Tajiks.

[Sapporo]

Can someone run an oracle on my results as well:

0% Oceanian
2.83% EEF
11.61% European
1.06% Amerindian
43.11% Central Asian
39.77% South Asian
0% East Asian
1.61% Siberian
0% SSA

Thanks in advance. :)

[SwampThing27]

Can someone run an oracle on my results as well:

0% Oceanian
2.83% EEF
11.61% European
1.06% Amerindian
43.11% Central Asian
39.77% South Asian
0% East Asian
1.61% Siberian
0% SSA

Thanks in advance. :)

Here you go:

[email protected] 7.89813524310039
[email protected] 8.16243368548865
[email protected] 9.64502589971898
[email protected] 15.4249436554044
[email protected] 16.6140445120579
[email protected] 17.6386109151026
[email protected] 18.4593725422125
[email protected] 20.4165619841466
[email protected] 20.6144378062237
[email protected] 20.6489433756356
[email protected] 24.6686567037202
[email protected] 25.9064393435361
[email protected] 28.0390493434567
[email protected] 28.5585415538959
[email protected] 29.5905376961917
[email protected] 30.012649310749
[email protected] 30.6718091633213
[email protected] 30.7485739173583
[email protected] 30.8024700876472
[email protected] 32.6752883507618

[SwampThing27]

Czechs are quite high in many oracle results. In my case it's on top, whereas my Czech ancestry represents only 1.8% of my known ancestry. Unfortunately, there are no German samples. In my case Czech seems to replace (North)German. I don't know why .... Any thoughts?

Yeah I have also noticed that Czech usually seems to fall in with the English, Scottish, Orcadian in a lot of my results as well.

Especially on these newer tests. Not so much on the older calculators.

[Dr_McNinja]

I am surprised that you, me, and Zahra have a smaller distance (larger overlap) with Tajik than Afghan Tajik. One usually associates Tajik as from Tajikstan, who are more E Eurasian shifted than Afghan Tajiks. I guess it is possible that the "Tajiks" may not be Tajikstan Tajiks.



The Afghan Tajik profile here has more East Eurasian than Tajik_Pomiri and Tadjik. Tajik_Pomiri has a higher European:EEF ratio and slightly more South Asian and Central Asian and the least East Asian.

[Sapporo]

Here you go:

[email protected] 7.89813524310039
[email protected] 8.16243368548865
[email protected] 9.64502589971898
[email protected] 15.4249436554044
[email protected] 16.6140445120579
[email protected] 17.6386109151026
[email protected] 18.4593725422125
[email protected] 20.4165619841466
[email protected] 20.6144378062237
[email protected] 20.6489433756356
[email protected] 24.6686567037202
[email protected] 25.9064393435361
[email protected] 28.0390493434567
[email protected] 28.5585415538959
[email protected] 29.5905376961917
[email protected] 30.012649310749
[email protected] 30.6718091633213
[email protected] 30.7485739173583
[email protected] 30.8024700876472
[email protected] 32.6752883507618

Much appreciated. Can you post the oracle mixed mode too? :)

[Sapporo]

The Afghan Tajik profile here has more East Eurasian than Tajik_Pomiri and Tadjik. Tajik_Pomiri has a higher European:EEF ratio and slightly more South Asian and Central Asian and the least East Asian.

Also, I am pretty sure the Tadjik are the Yunusbayev Tajiks from Tajikistan. Probably urban Tajiks from Dushanbe.

[SwampThing27]

Much appreciated. Can you post the oracle mixed mode too? :)

The spreadsheet im using only has the single population unfortunately.

[Dr_McNinja]

Here you go,

Least-squares method.

Using 1 population approximation:
1 Pathan @ 7.898814
2 GujaratiA @ 8.1596
3 Burusho @ 9.650363
4 GujaratiB @ 15.429579
5 Kalash @ 16.613483
6 Balochi @ 17.636337
7 Brahmin_UP @ 18.455529
8 Brahmin_TN @ 20.414645
9 Brahui @ 20.61777
10 Kshatriya @ 20.645774
11 GujaratiC @ 24.665332
12 Tajik_Pomiri @ 25.907734
13 Afghan_Tadjik @ 28.045035
14 Afghan_Uzbeki @ 28.560988
15 Tadjik @ 29.598063
16 Velamas @ 30.017858
17 Muslim_India @ 30.673887
18 Punjabi @ 30.74217
19 GujaratiD @ 30.797447
20 Dharkar @ 32.67861
206 iterations.

Using 2 populations approximation:
1 Brahmin_UP+Kalash @ 2.550768
2 GujaratiA+Pathan @ 3.29333
3 GujaratiB+Kalash @ 3.515754
4 Kalash+Kshatriya @ 3.640468
5 GujaratiA+Kalash @ 4.443692
6 Brahmin_TN+Kalash @ 4.771226
7 Tajik_Pomiri+Velamas @ 5.03721
8 Burusho+GujaratiA @ 5.128943
9 GujaratiB+Pathan @ 5.31473
10 GujaratiC+Tajik_Pomiri @ 5.75224
11 Brahmin_TN+Tajik_Pomiri @ 5.816695
12 GujaratiC+Kalash @ 6.102224
13 GujaratiD+Tajik_Pomiri @ 6.263716
14 Balochi+GujaratiA @ 6.6441
15 Balochi+GujaratiB @ 6.720446
16 Balochi+Brahmin_UP @ 6.73898
17 Brahmin_UP+Pathan @ 6.883591
18 Burusho+GujaratiB @ 6.952279
19 GujaratiB+Tajik_Pomiri @ 7.153898
20 Brahui+GujaratiB @ 7.308663
21321 iterations.

Using 3 populations approximation:
1 50% Brahmin_TN +25% Kalash +25% Tajik_Pomiri @ 1.555055
2 50% GujaratiA +25% Kalash +25% Pathan @ 1.767788
3 50% Kalash +25% Hakkipikki +25% Tajik_Pomiri @ 1.936673
4 50% GujaratiA +25% Burusho +25% Kalash @ 2.014691
5 50% Kalash +25% Sakilli +25% Tajik_Pomiri @ 2.201155
6 50% Kalash +25% Chamar +25% Tajik_Pomiri @ 2.263859
7 50% GujaratiA +25% GujaratiA +25% Kalash @ 2.296948
8 50% Kalash +25% Kanjar +25% Pathan @ 2.389608
9 50% Pathan +25% GujaratiC +25% Kalash @ 2.406637
10 50% Kalash +25% North_Kannadi +25% Tajik_Pomiri @ 2.40846
11 50% GujaratiB +25% Kalash +25% Tajik_Pomiri @ 2.426586
12 50% Pathan +25% Kalash +25% Muslim_India @ 2.4412
13 50% Pathan +25% Kalash +25% Punjabi @ 2.455647
14 50% Kalash +25% GujaratiA +25% Kshatriya @ 2.461535
15 50% Kalash +25% Pathan +25% Uttar_Pradesh @ 2.476067
16 50% Kalash +25% Brahmin_UP +25% GujaratiA @ 2.510236
17 50% Pathan +25% Dharkar +25% Kalash @ 2.514882
18 50% Brahmin_UP +25% Kalash +25% Kalash @ 2.550768
19 50% Kalash +25% Burusho +25% Kanjar @ 2.555518
20 50% Pathan +25% Kalash +25% Kshatriya @ 2.567526
1355746 iterations.

Using 4 populations approximation:
1 GujaratiA+Kalash+Tajik_Pomiri+Velamas @ 1.007816
2 GujaratiA+GujaratiB+Kalash+Pathan @ 1.190279
3 Brahmin_UP+GujaratiA+Kalash+Pathan @ 1.457534
4 Brahmin_TN+GujaratiB+Kalash+Tajik_Pomiri @ 1.458515
5 GujaratiB+GujaratiC+Kalash+Tajik_Pomiri @ 1.466053
6 GujaratiA+GujaratiD+Kalash+Tajik_Pomiri @ 1.494333
7 Brahmin_TN+Brahmin_TN+Kalash+Tajik_Pomiri @ 1.555055
8 GujaratiA+GujaratiA+Kalash+Pathan @ 1.767788
9 Burusho+GujaratiA+GujaratiB+Kalash @ 1.872865
10 GujaratiB+Kalash+Tajik_Pomiri+Velamas @ 1.881389
11 Hakkipikki+Kalash+Kalash+Tajik_Pomiri @ 1.936673
12 GujaratiA+Kalash+Kshatriya+Pathan @ 1.936848
13 Brahmin_TN+Kalash+Kshatriya+Tajik_Pomiri @ 1.990098
14 Burusho+GujaratiA+GujaratiA+Kalash @ 2.014691
15 GujaratiA+Kalash+Kurumba+Tajik_Pomiri @ 2.035585
16 Brahmin_TN+GujaratiC+Kalash+Tajik_Pomiri @ 2.1038
17 Brahmin_TN+Brahmin_UP+Kalash+Tajik_Pomiri @ 2.157431
18 Kalash+Kalash+Sakilli+Tajik_Pomiri @ 2.201155
19 GujaratiB+Kalash+Kshatriya+Tajik_Pomiri @ 2.211523
20 Brahmin_TN+GujaratiA+Kalash+Pathan @ 2.238881
21 GujaratiB+GujaratiD+Kalash+Tajik_Pomiri @ 2.252193
22 Chamar+Kalash+Kalash+Tajik_Pomiri @ 2.263859
23 GujaratiA+GujaratiA+GujaratiA+Kalash @ 2.296948
24 Burusho+GujaratiC+Kalash+Pathan @ 2.343955
25 Kalash+Kalash+Kanjar+Pathan @ 2.389608
26 GujaratiA+GujaratiC+Kalash+Tajik_Pomiri @ 2.398451
27 GujaratiC+Kalash+Pathan+Pathan @ 2.406637
28 Kalash+Kalash+North_Kannadi+Tajik_Pomiri @ 2.40846
29 GujaratiB+GujaratiB+Kalash+Tajik_Pomiri @ 2.426586
30 Kalash+Muslim_India+Pathan+Pathan @ 2.4412
31 Kalash+Pathan+Pathan+Punjabi @ 2.455647
32 GujaratiA+Kalash+Kalash+Kshatriya @ 2.461535
33 Kalash+Kalash+Pathan+Uttar_Pradesh @ 2.476067
34 Brahmin_UP+Burusho+GujaratiA+Kalash @ 2.498927
35 Brahmin_UP+GujaratiA+Kalash+Kalash @ 2.510236
36 Dharkar+Kalash+Pathan+Pathan @ 2.514882
37 Brahmin_UP+GujaratiC+Kalash+Tajik_Pomiri @ 2.549055
38 Brahmin_UP+Brahmin_UP+Kalash+Kalash @ 2.550768
39 Kalash+Pathan+Piramalai+Tajik_Pomiri @ 2.553009
40 Balochi+Brahmin_UP+GujaratiA+Kalash @ 2.554885
3011752 iterations.


Gaussian method.
Noise dispersion set to 0.584552

Using 1 population approximation:
1 GujaratiA @ 3.353682
2 Pathan @ 5.192063
3 GujaratiB @ 6.043982
4 Brahmin_UP @ 6.699173
5 Burusho @ 7.620534
6 Kshatriya @ 7.630163
7 Brahmin_TN @ 8.42581
8 Kalash @ 8.581043
9 Balochi @ 8.843817
10 GujaratiC @ 9.403971
11 Brahui @ 10.392164
12 Punjabi @ 11.713544
13 Muslim_India @ 11.89645
14 Tajik_Pomiri @ 12.257642
15 Dharkar @ 12.374613
16 Kanjar @ 13.113845
17 GujaratiD @ 13.43245
18 Afghan_Tadjik @ 13.901802
19 Afghan_Uzbeki @ 13.963757
20 Tadjik @ 14.945298
206 iterations.

Using 2 populations approximation:
1 GujaratiA+Kalash @ 2.794539
2 Brahmin_UP+Kalash @ 3.189186
3 GujaratiA+GujaratiA @ 3.353682
4 GujaratiA+Pathan @ 3.592368
5 GujaratiB+Kalash @ 3.742743
6 Kalash+Kshatriya @ 3.765642
7 GujaratiB+Pathan @ 3.915128
8 Brahmin_TN+Kalash @ 4.002156
9 Brahmin_UP+Pathan @ 4.218094
10 GujaratiA+GujaratiB @ 4.560063
11 Kshatriya+Pathan @ 4.570392
12 GujaratiC+Kalash @ 4.698946
13 Tajik_Pomiri+Velamas @ 4.740867
14 GujaratiC+Pathan @ 4.83577
15 Kalash+Punjabi @ 4.836763
16 Brahmin_TN+Pathan @ 4.846028
17 Balochi+GujaratiA @ 4.968579
18 GujaratiD+Tajik_Pomiri @ 4.975425
19 Brahmin_UP+GujaratiA @ 5.010775
20 Kalash+Pathan @ 5.025246
21321 iterations.

Using 3 populations approximation:
1 50% GujaratiA +25% GujaratiA +25% Kalash @ 1.976052
2 50% GujaratiA +25% GujaratiB +25% Kalash @ 2.567418
3 50% GujaratiA +25% Brahmin_UP +25% Kalash @ 2.687904
4 50% GujaratiA +25% Kalash +25% Pathan @ 2.725717
5 50% GujaratiA +25% Kalash +25% Kalash @ 2.794539
6 50% Kalash +25% Brahmin_UP +25% GujaratiA @ 2.798931
7 50% Kalash +25% Kanjar +25% Pathan @ 2.934318
8 50% GujaratiA +25% Kalash +25% Kshatriya @ 2.944573
9 50% GujaratiA +25% Brahmin_TN +25% Kalash @ 2.968332
10 50% GujaratiB +25% Kalash +25% Pathan @ 2.985535
11 50% Kalash +25% GujaratiA +25% Kshatriya @ 2.996112
12 50% Kalash +25% GujaratiA +25% GujaratiB @ 3.0419
13 50% Kalash +25% Brahmin_TN +25% GujaratiA @ 3.071312
14 50% GujaratiA +25% GujaratiC +25% Kalash @ 3.074561
15 50% Kalash +25% GujaratiD +25% Pathan @ 3.102963
16 50% Kalash +25% GujaratiC +25% Pathan @ 3.114027
17 50% Brahmin_UP +25% Kalash +25% Pathan @ 3.123262
18 50% Kalash +25% GujaratiA +25% GujaratiC @ 3.124749
19 50% Brahmin_UP +25% Kalash +25% Kalash @ 3.189186
20 50% GujaratiA +25% GujaratiA +25% Pathan @ 3.215744
3542806 iterations.

Using 4 populations approximation:
1 GujaratiA+GujaratiA+GujaratiA+Kalash @ 1.976052
2 GujaratiA+GujaratiA+GujaratiB+Kalash @ 2.567418
3 Brahmin_UP+GujaratiA+GujaratiA+Kalash @ 2.687904
4 GujaratiA+GujaratiA+Kalash+Pathan @ 2.725717
5 GujaratiA+GujaratiB+Kalash+Pathan @ 2.726203
6 Brahmin_UP+GujaratiA+Kalash+Pathan @ 2.784487
7 GujaratiA+GujaratiA+Kalash+Kalash @ 2.794539
8 Brahmin_UP+GujaratiA+Kalash+Kalash @ 2.798931
9 GujaratiA+GujaratiC+Kalash+Pathan @ 2.865447
10 Kalash+Kalash+Kanjar+Pathan @ 2.934318
11 GujaratiA+Kalash+Kshatriya+Pathan @ 2.938594
12 GujaratiA+GujaratiA+Kalash+Kshatriya @ 2.944573
13 Brahmin_TN+GujaratiA+GujaratiA+Kalash @ 2.968332
14 GujaratiB+GujaratiB+Kalash+Pathan @ 2.985535
15 GujaratiA+Kalash+Kalash+Kshatriya @ 2.996112
16 Brahmin_UP+GujaratiB+Kalash+Pathan @ 3.004904
17 Brahmin_TN+GujaratiA+Kalash+Pathan @ 3.040344
18 GujaratiA+GujaratiB+Kalash+Kalash @ 3.0419
19 Brahmin_TN+GujaratiA+Kalash+Kalash @ 3.071312
20 GujaratiA+GujaratiA+GujaratiC+Kalash @ 3.074561
21 GujaratiD+Kalash+Kalash+Pathan @ 3.102963
22 GujaratiC+Kalash+Kalash+Pathan @ 3.114027
23 Brahmin_UP+Brahmin_UP+Kalash+Pathan @ 3.123262
24 GujaratiA+GujaratiC+Kalash+Kalash @ 3.124749
25 GujaratiA+GujaratiD+Kalash+Pathan @ 3.157463
26 Brahmin_UP+Brahmin_UP+Kalash+Kalash @ 3.189186
27 GujaratiA+GujaratiA+GujaratiA+Pathan @ 3.215744
28 GujaratiB+Kalash+Kshatriya+Pathan @ 3.217096
29 Dharkar+Kalash+Kalash+Pathan @ 3.26085
30 GujaratiA+Kalash+Pathan+Velamas @ 3.274869
31 Kalash+Kalash+Kol+Pathan @ 3.279396
32 Brahmin_UP+Kalash+Kalash+Pathan @ 3.283623
33 Kalash+Kalash+Pathan+Velamas @ 3.292244
34 GujaratiA+Kalash+Kanjar+Pathan @ 3.295048
35 GujaratiA+GujaratiB+GujaratiB+Kalash @ 3.299174
36 Kalash+Kalash+Kshatriya+Pathan @ 3.311399
37 Brahmin_UP+Kalash+Kshatriya+Pathan @ 3.314724
38 GujaratiA+Kalash+Kalash+Velamas @ 3.323695
39 Brahmin_UP+GujaratiA+GujaratiB+Kalash @ 3.326487
40 Kalash+Kalash+Pathan+Punjabi @ 3.333552
39689958 iterations.

[Sapporo]

@Dr_McNinja

Thank you. Wonder why David didn't include the Northern Afghan Pashtuns. Cool that he included the Punjabi Lahore (PJL) though.

[randwulf]

My father K9 (USA immigrant ancestors all from West and South Germany, possible somewhat recent East Asian admixture per analysis by Davidski):

Oceanian 0.005889
EEF 0.358446
European 0.462375
Amerindian 0.008640
Central_Asian 0.139394
South_Asian 0.000010
East_Asian 0.000010
Siberian 0.017832
Sub-Saharan 0.007383

[email protected] 3.09662448509679
[email protected] 7.1443950760159
[email protected] 7.15711935697596
[email protected] 7.18519365308966
[email protected] 7.90345044165838
[email protected] 8.46929483874691
[email protected] 9.60650277046636
[email protected] 9.75098774650286
[email protected] 10.0743182443962
[email protected] 10.6940477890133
[email protected] 10.8512370975476
[email protected] 11.8174411616898
[email protected] 12.6382275536604
[email protected] 13.362143172538
[email protected] 13.6497311697662
[email protected] 13.8149978125095
[email protected] 14.7565934481367
[email protected] 14.8491900133172
[email protected] 14.858720939233
[email protected] 15.5113945628685

K6:

Yamnaya_related 0.369217
WHG_extra 0.032378
ENA 0.011175
Middle_Eastern 0.079930
Pre-Yamnaya 0.491178
Sub-Saharan 0.016122

[MonkeyDLuffy]

@Dr_McNinja

Thank you. Wonder why David didn't include the Northern Afghan Pashtuns. Cool that he included the Punjabi Lahore (PJL) though.

why gujarati is more closer to us than a Punjabi on oracle?

[Rukha]

I am surprised that you, me, and Zahra have a smaller distance (larger overlap) with Tajik than Afghan Tajik. One usually associates Tajik as from Tajikstan, who are more E Eurasian shifted than Afghan Tajiks. I guess it is possible that the "Tajiks" may not be Tajikstan Tajiks.




The Tajiks are the Yunusbayev Tajiks from Tajikistan. I believe the Afghan Tajiks are from Kunduz which is a multiethnic province where intermarriage with Uzbeks is more common.

[surbakhunWeesste]

Here you go,



Hey, Can you please make the mixed oracle for my result ?!

[Sapporo]

why gujarati is more closer to us than a Punjabi on oracle?

Gujarati_A are the most West Asian shifted South Asians in the K9 run. Likely Brahmins and maybe some Kutchi/Sindhi origin types like Lohanas. The PJL are the Punjabi_Lahore samples and are likely of chura/chamar type backgrounds based on how south shifted they are. They likely aren't of normal caste/tribal backgrounds.

[Dr_McNinja]

Hey, Can you please make the mixed oracle for my result ?!

Least-squares method.

Using 1 population approximation:
1 Brahui @ 9.019974
2 Balochi @ 10.372001
3 Kalash @ 14.68817
4 Tajik_Pomiri @ 14.863355
5 Pathan @ 15.828733
6 Tadjik @ 16.055885
7 Afghan_Uzbeki @ 17.652627
8 Afghan_Tadjik @ 17.742248
9 Burusho @ 18.948787
10 Lezgin @ 23.126793
11 Chechen @ 24.197285
12 Kumyk @ 25.015305
13 Adygei @ 25.555249
14 North_Ossetian @ 25.768469
15 Balkar @ 25.811462
16 Iranian @ 28.075719
17 Turkmen @ 28.544735
18 Abkhasian @ 29.785671
19 GujaratiA @ 30.335932
20 Nogay @ 30.798379
206 iterations.

Using 2 populations approximation:
1 Balochi+Tajik_Pomiri @ 6.681185
2 Brahui+Tajik_Pomiri @ 6.902713
3 Kalash+Kumyk @ 7.022921
4 Balochi+Tadjik @ 7.424814
5 Lezgin+Pathan @ 7.464502
6 Kalash+North_Ossetian @ 7.533751
7 Balkar+Kalash @ 7.539839
8 Iranian+Kalash @ 7.669962
9 Adygei+Kalash @ 7.678018
10 Burusho+Lezgin @ 7.755237
11 Kalash+Tadjik @ 7.933917
12 Afghan_Uzbeki+Kalash @ 8.171141
13 Brahui+Tadjik @ 8.222013
14 Brahui+Kalash @ 8.346023
15 Chechen+Kalash @ 8.403057
16 Chechen+Pathan @ 8.448132
17 Abkhasian+GujaratiA @ 8.516358
18 Balochi+Lezgin @ 8.543704
19 Adygei+Pathan @ 8.67047
20 Afghan_Tadjik+Kalash @ 8.728242
21321 iterations.

Using 3 populations approximation:
1 50% Kalash +25% Abkhasian +25% Afghan_Tadjik @ 2.588737
2 50% Kalash +25% Afghan_Tadjik +25% Georgian @ 2.595326
3 50% Kalash +25% Abkhasian +25% Afghan_Uzbeki @ 2.605752
4 50% Kalash +25% Afghan_Uzbeki +25% Georgian @ 2.731136
5 50% Kalash +25% Balkar +25% Brahui @ 2.828979
6 50% Kalash +25% Brahui +25% North_Ossetian @ 2.839647
7 50% Kalash +25% Brahui +25% Kumyk @ 3.008487
8 50% Kalash +25% Balkar +25% Balochi @ 3.011741
9 50% Balochi +25% Balkar +25% Kalash @ 3.013321
10 50% Balochi +25% Kalash +25% North_Ossetian @ 3.015369
11 50% Kalash +25% Balochi +25% North_Ossetian @ 3.030007
12 50% Kalash +25% Burusho +25% Georgian @ 3.154063
13 50% Kalash +25% Adygei +25% Brahui @ 3.21541
14 50% Kalash +25% Balochi +25% Kumyk @ 3.25718
15 50% Balochi +25% Chechen +25% Kalash @ 3.314982
16 50% Balochi +25% Adygei +25% Kalash @ 3.327063
17 50% Kalash +25% Adygei +25% Balochi @ 3.41706
18 50% Balochi +25% Kalash +25% Lezgin @ 3.422105
19 50% Balochi +25% Kalash +25% Kumyk @ 3.570004
20 50% Kalash +25% Abkhasian +25% Burusho @ 3.598243
2623813 iterations.

Using 4 populations approximation:
1 Abkhasian+Afghan_Tadjik+Kalash+Kalash @ 2.588737
2 Afghan_Tadjik+Georgian+Kalash+Kalash @ 2.595326
3 Abkhasian+Afghan_Uzbeki+Kalash+Kalash @ 2.605752
4 Afghan_Uzbeki+Georgian+Kalash+Kalash @ 2.731136
5 Balkar+Brahui+Kalash+Kalash @ 2.828979
6 Brahui+Kalash+Kalash+North_Ossetian @ 2.839647
7 Brahui+Kalash+Kalash+Kumyk @ 3.008487
8 Balkar+Balochi+Kalash+Kalash @ 3.011741
9 Balkar+Balochi+Balochi+Kalash @ 3.013321
10 Balochi+Balochi+Kalash+North_Ossetian @ 3.015369
11 Balochi+Kalash+Kalash+North_Ossetian @ 3.030007
12 Burusho+Georgian+Kalash+Kalash @ 3.154063
13 Adygei+Brahui+Kalash+Kalash @ 3.21541
14 Balochi+Kalash+Kalash+Kumyk @ 3.25718
15 Balochi+Brahui+Kalash+North_Ossetian @ 3.292583
16 Balkar+Balochi+Brahui+Kalash @ 3.298279
17 Balochi+Balochi+Chechen+Kalash @ 3.314982
18 Abkhasian+Brahui+Burusho+Kalash @ 3.318565
19 Adygei+Balochi+Balochi+Kalash @ 3.327063
20 Abkhasian+Balochi+Burusho+Kalash @ 3.337826
21 Balochi+Brahui+Kalash+Lezgin @ 3.403725
22 Adygei+Balochi+Kalash+Kalash @ 3.41706
23 Balochi+Brahui+Chechen+Kalash @ 3.420798
24 Balochi+Balochi+Kalash+Lezgin @ 3.422105
25 Adygei+Balochi+Brahui+Kalash @ 3.549353
26 Balochi+Balochi+Kalash+Kumyk @ 3.570004
27 Abkhasian+Burusho+Kalash+Kalash @ 3.598243
28 Kalash+Kalash+Kalash+Turk_Trabzon @ 3.655663
29 Afghan_Tadjik+Kalash+Kalash+Kurdish @ 3.673434
30 Brahui+Brahui+Kalash+Lezgin @ 3.738335
31 Balochi+Burusho+Georgian+Kalash @ 3.746477
32 Balochi+Brahui+Kalash+Kumyk @ 3.748693
33 Brahui+Kalash+North_Ossetian+Pathan @ 3.753176
34 Balkar+Brahui+Kalash+Pathan @ 3.791962
35 Afghan_Uzbeki+Kalash+Kalash+Kurdish @ 3.802701
36 Afghan_Tadjik+Balochi+Kalash+Lezgin @ 3.806921
37 Brahui+Burusho+Georgian+Kalash @ 3.815362
38 Armenian+Kalash+Kalash+Kalash @ 3.818001
39 Abkhasian+Brahui+Kalash+Kalash @ 3.827946
40 Balochi+Kalash+North_Ossetian+Pathan @ 3.838084
15990325 iterations.


Gaussian method.
Noise dispersion set to 0.584552

Using 1 population approximation:
1 Balochi @ 7.957922
2 Tajik_Pomiri @ 8.414437
3 Pathan @ 8.440801
4 Brahui @ 9.183488
5 Tadjik @ 9.719094
6 Afghan_Uzbeki @ 10.068109
7 Afghan_Tadjik @ 10.393198
8 Burusho @ 10.894066
9 Iranian @ 14.338509
10 Turkmen @ 15.106245
11 GujaratiA @ 15.211257
12 Kurdish @ 16.192992
13 Uzbek @ 16.418128
14 Afghan_Turkmen @ 16.755715
15 Uzbeki @ 17.497433
16 Brahmin_UP @ 18.855163
17 Brahmin_TN @ 19.481914
18 GujaratiB @ 19.558794
19 Kshatriya @ 19.941163
20 Uygur @ 21.233099
206 iterations.

Using 2 populations approximation:
1 Kalash+Kumyk @ 5.254007
2 Kalash+North_Ossetian @ 5.383975
3 Adygei+Kalash @ 5.392795
4 Balkar+Kalash @ 5.461274
5 GujaratiA+North_Ossetian @ 5.581013
6 Adygei+GujaratiA @ 5.632544
7 Adygei+Pathan @ 5.678671
8 Balkar+GujaratiA @ 5.68211
9 North_Ossetian+Pathan @ 5.730997
10 Balkar+Pathan @ 5.819486
11 Balochi+Tajik_Pomiri @ 5.834807
12 GujaratiB+North_Ossetian @ 5.936742
13 Balochi+Tadjik @ 5.952945
14 Adygei+GujaratiB @ 5.966643
15 Kumyk+Pathan @ 5.974979
16 Balkar+GujaratiB @ 6.03199
17 Burusho+Lezgin @ 6.148676
18 Chechen+Pathan @ 6.152444
19 Chechen+Kalash @ 6.161303
20 GujaratiA+Kumyk @ 6.184081
21321 iterations.

Using 3 populations approximation:
1 50% Kalash +25% Balochi +25% North_Ossetian @ 4.040978
2 50% Kalash +25% Afghan_Uzbeki +25% Georgian @ 4.047966
3 50% Kalash +25% Balkar +25% Balochi @ 4.066488
4 50% Balochi +25% Kalash +25% North_Ossetian @ 4.070616
5 50% Balochi +25% Balkar +25% Kalash @ 4.101907
6 50% Kalash +25% Burusho +25% Georgian @ 4.103662
7 50% North_Ossetian +25% Kalash +25% Velamas @ 4.158732
8 50% Adygei +25% Kalash +25% Velamas @ 4.208915
9 50% Kalash +25% Balochi +25% Kumyk @ 4.232104
10 50% Kalash +25% Abkhasian +25% Afghan_Uzbeki @ 4.236385
11 50% Kalash +25% Georgian +25% Tadjik @ 4.244425
12 50% Kalash +25% Afghan_Tadjik +25% Georgian @ 4.289555
13 50% Balkar +25% Kalash +25% Velamas @ 4.289562
14 50% Balochi +25% Kalash +25% Kumyk @ 4.31676
15 50% Kalash +25% Abkhasian +25% Burusho @ 4.341414
16 50% Adygei +25% Brahmin_TN +25% Kalash @ 4.361319
17 50% Kalash +25% Abkhasian +25% Tadjik @ 4.391343
18 50% Kalash +25% Burusho +25% Turk_Trabzon @ 4.402696
19 50% North_Ossetian +25% Brahmin_TN +25% Kalash @ 4.406413
20 50% Kalash +25% Armenian +25% Burusho @ 4.454478
3962881 iterations.

Using 4 populations approximation:
1 Balochi+Kalash+Kalash+North_Ossetian @ 4.040978
2 Afghan_Uzbeki+Georgian+Kalash+Kalash @ 4.047966
3 Balkar+Balochi+Kalash+Kalash @ 4.066488
4 Balochi+Balochi+Kalash+North_Ossetian @ 4.070616
5 Balkar+Balochi+Balochi+Kalash @ 4.101907
6 Burusho+Georgian+Kalash+Kalash @ 4.103662
7 Adygei+Kalash+North_Ossetian+Velamas @ 4.110138
8 Kalash+North_Ossetian+North_Ossetian+Velamas @ 4.158732
9 Adygei+Balkar+Kalash+Velamas @ 4.169785
10 Adygei+Adygei+Kalash+Velamas @ 4.208915
11 Balochi+Kalash+North_Ossetian+Pathan @ 4.215849
12 Balkar+Kalash+North_Ossetian+Velamas @ 4.224765
13 Abkhasian+Brahmin_TN+Kalash+North_Ossetian @ 4.23024
14 Balochi+Kalash+Kalash+Kumyk @ 4.232104
15 Abkhasian+Afghan_Uzbeki+Kalash+Kalash @ 4.236385
16 Georgian+Kalash+Kalash+Tadjik @ 4.244425
17 Balkar+Balochi+Kalash+Pathan @ 4.247891
18 Abkhasian+Balkar+Brahmin_TN+Kalash @ 4.271003
19 Afghan_Tadjik+Georgian+Kalash+Kalash @ 4.289555
20 Balkar+Balkar+Kalash+Velamas @ 4.289562
21 Abkhasian+Balochi+Burusho+Kalash @ 4.307219
22 Balochi+Balochi+Kalash+Kumyk @ 4.31676
23 Adygei+Brahmin_TN+Kalash+North_Ossetian @ 4.323758
24 Abkhasian+Kalash+North_Ossetian+Velamas @ 4.335433
25 Abkhasian+Burusho+Kalash+Kalash @ 4.341414
26 Balochi+Burusho+Georgian+Kalash @ 4.344611
27 Abkhasian+GujaratiB+Kalash+North_Ossetian @ 4.354686
28 Chechen+Kalash+North_Ossetian+Velamas @ 4.355072
29 Brahmin_TN+Georgian+Kalash+North_Ossetian @ 4.359756
30 Adygei+Adygei+Brahmin_TN+Kalash @ 4.361319
31 Abkhasian+Balkar+Kalash+Velamas @ 4.366911
32 Adygei+Balkar+Brahmin_TN+Kalash @ 4.381165
33 Kalash+Lezgin+North_Ossetian+Velamas @ 4.381951
34 Abkhasian+Balkar+GujaratiB+Kalash @ 4.383349
35 Burusho+Georgian+Kalash+Pathan @ 4.387543
36 Abkhasian+Kalash+Kalash+Tadjik @ 4.391343
37 Balkar+Brahmin_TN+Georgian+Kalash @ 4.393343
38 Balkar+Chechen+Kalash+Velamas @ 4.398421
39 Burusho+Kalash+Kalash+Turk_Trabzon @ 4.402696
40 Brahmin_TN+Kalash+North_Ossetian+North_Ossetian @ 4.406413
57108943 iterations.

[surbakhunWeesste]

Least-squares method.

Using 1 population approximation:
1 Brahui @ 9.019974
2 Balochi @ 10.372001
3 Kalash @ 14.68817
4 Tajik_Pomiri @ 14.863355
5 Pathan @ 15.828733
6 Tadjik @ 16.055885
7 Afghan_Uzbeki @ 17.652627
8 Afghan_Tadjik @ 17.742248
9 Burusho @ 18.948787
10 Lezgin @ 23.126793
11 Chechen @ 24.197285
12 Kumyk @ 25.015305
13 Adygei @ 25.555249
14 North_Ossetian @ 25.768469
15 Balkar @ 25.811462
16 Iranian @ 28.075719
17 Turkmen @ 28.544735
18 Abkhasian @ 29.785671
19 GujaratiA @ 30.335932
20 Nogay @ 30.798379
206 iterations.

Using 2 populations approximation:
1 Balochi+Tajik_Pomiri @ 6.681185
2 Brahui+Tajik_Pomiri @ 6.902713
3 Kalash+Kumyk @ 7.022921
4 Balochi+Tadjik @ 7.424814
5 Lezgin+Pathan @ 7.464502
6 Kalash+North_Ossetian @ 7.533751
7 Balkar+Kalash @ 7.539839
8 Iranian+Kalash @ 7.669962
9 Adygei+Kalash @ 7.678018
10 Burusho+Lezgin @ 7.755237
11 Kalash+Tadjik @ 7.933917
12 Afghan_Uzbeki+Kalash @ 8.171141
13 Brahui+Tadjik @ 8.222013
14 Brahui+Kalash @ 8.346023
15 Chechen+Kalash @ 8.403057
16 Chechen+Pathan @ 8.448132
17 Abkhasian+GujaratiA @ 8.516358
18 Balochi+Lezgin @ 8.543704
19 Adygei+Pathan @ 8.67047
20 Afghan_Tadjik+Kalash @ 8.728242
21321 iterations.

Using 3 populations approximation:
1 50% Kalash +25% Abkhasian +25% Afghan_Tadjik @ 2.588737
2 50% Kalash +25% Afghan_Tadjik +25% Georgian @ 2.595326
3 50% Kalash +25% Abkhasian +25% Afghan_Uzbeki @ 2.605752
4 50% Kalash +25% Afghan_Uzbeki +25% Georgian @ 2.731136
5 50% Kalash +25% Balkar +25% Brahui @ 2.828979
6 50% Kalash +25% Brahui +25% North_Ossetian @ 2.839647
7 50% Kalash +25% Brahui +25% Kumyk @ 3.008487
8 50% Kalash +25% Balkar +25% Balochi @ 3.011741
9 50% Balochi +25% Balkar +25% Kalash @ 3.013321
10 50% Balochi +25% Kalash +25% North_Ossetian @ 3.015369
11 50% Kalash +25% Balochi +25% North_Ossetian @ 3.030007
12 50% Kalash +25% Burusho +25% Georgian @ 3.154063
13 50% Kalash +25% Adygei +25% Brahui @ 3.21541
14 50% Kalash +25% Balochi +25% Kumyk @ 3.25718
15 50% Balochi +25% Chechen +25% Kalash @ 3.314982
16 50% Balochi +25% Adygei +25% Kalash @ 3.327063
17 50% Kalash +25% Adygei +25% Balochi @ 3.41706
18 50% Balochi +25% Kalash +25% Lezgin @ 3.422105
19 50% Balochi +25% Kalash +25% Kumyk @ 3.570004
20 50% Kalash +25% Abkhasian +25% Burusho @ 3.598243
2623813 iterations.

Using 4 populations approximation:
1 Abkhasian+Afghan_Tadjik+Kalash+Kalash @ 2.588737
2 Afghan_Tadjik+Georgian+Kalash+Kalash @ 2.595326
3 Abkhasian+Afghan_Uzbeki+Kalash+Kalash @ 2.605752
4 Afghan_Uzbeki+Georgian+Kalash+Kalash @ 2.731136
5 Balkar+Brahui+Kalash+Kalash @ 2.828979
6 Brahui+Kalash+Kalash+North_Ossetian @ 2.839647
7 Brahui+Kalash+Kalash+Kumyk @ 3.008487
8 Balkar+Balochi+Kalash+Kalash @ 3.011741
9 Balkar+Balochi+Balochi+Kalash @ 3.013321
10 Balochi+Balochi+Kalash+North_Ossetian @ 3.015369
11 Balochi+Kalash+Kalash+North_Ossetian @ 3.030007
12 Burusho+Georgian+Kalash+Kalash @ 3.154063
13 Adygei+Brahui+Kalash+Kalash @ 3.21541
14 Balochi+Kalash+Kalash+Kumyk @ 3.25718
15 Balochi+Brahui+Kalash+North_Ossetian @ 3.292583
16 Balkar+Balochi+Brahui+Kalash @ 3.298279
17 Balochi+Balochi+Chechen+Kalash @ 3.314982
18 Abkhasian+Brahui+Burusho+Kalash @ 3.318565
19 Adygei+Balochi+Balochi+Kalash @ 3.327063
20 Abkhasian+Balochi+Burusho+Kalash @ 3.337826
21 Balochi+Brahui+Kalash+Lezgin @ 3.403725
22 Adygei+Balochi+Kalash+Kalash @ 3.41706
23 Balochi+Brahui+Chechen+Kalash @ 3.420798
24 Balochi+Balochi+Kalash+Lezgin @ 3.422105
25 Adygei+Balochi+Brahui+Kalash @ 3.549353
26 Balochi+Balochi+Kalash+Kumyk @ 3.570004
27 Abkhasian+Burusho+Kalash+Kalash @ 3.598243
28 Kalash+Kalash+Kalash+Turk_Trabzon @ 3.655663
29 Afghan_Tadjik+Kalash+Kalash+Kurdish @ 3.673434
30 Brahui+Brahui+Kalash+Lezgin @ 3.738335
31 Balochi+Burusho+Georgian+Kalash @ 3.746477
32 Balochi+Brahui+Kalash+Kumyk @ 3.748693
33 Brahui+Kalash+North_Ossetian+Pathan @ 3.753176
34 Balkar+Brahui+Kalash+Pathan @ 3.791962
35 Afghan_Uzbeki+Kalash+Kalash+Kurdish @ 3.802701
36 Afghan_Tadjik+Balochi+Kalash+Lezgin @ 3.806921
37 Brahui+Burusho+Georgian+Kalash @ 3.815362
38 Armenian+Kalash+Kalash+Kalash @ 3.818001
39 Abkhasian+Brahui+Kalash+Kalash @ 3.827946
40 Balochi+Kalash+North_Ossetian+Pathan @ 3.838084
15990325 iterations.


Gaussian method.
Noise dispersion set to 0.584552

Using 1 population approximation:
1 Balochi @ 7.957922
2 Tajik_Pomiri @ 8.414437
3 Pathan @ 8.440801
4 Brahui @ 9.183488
5 Tadjik @ 9.719094
6 Afghan_Uzbeki @ 10.068109
7 Afghan_Tadjik @ 10.393198
8 Burusho @ 10.894066
9 Iranian @ 14.338509
10 Turkmen @ 15.106245
11 GujaratiA @ 15.211257
12 Kurdish @ 16.192992
13 Uzbek @ 16.418128
14 Afghan_Turkmen @ 16.755715
15 Uzbeki @ 17.497433
16 Brahmin_UP @ 18.855163
17 Brahmin_TN @ 19.481914
18 GujaratiB @ 19.558794
19 Kshatriya @ 19.941163
20 Uygur @ 21.233099
206 iterations.

Using 2 populations approximation:
1 Kalash+Kumyk @ 5.254007
2 Kalash+North_Ossetian @ 5.383975
3 Adygei+Kalash @ 5.392795
4 Balkar+Kalash @ 5.461274
5 GujaratiA+North_Ossetian @ 5.581013
6 Adygei+GujaratiA @ 5.632544
7 Adygei+Pathan @ 5.678671
8 Balkar+GujaratiA @ 5.68211
9 North_Ossetian+Pathan @ 5.730997
10 Balkar+Pathan @ 5.819486
11 Balochi+Tajik_Pomiri @ 5.834807
12 GujaratiB+North_Ossetian @ 5.936742
13 Balochi+Tadjik @ 5.952945
14 Adygei+GujaratiB @ 5.966643
15 Kumyk+Pathan @ 5.974979
16 Balkar+GujaratiB @ 6.03199
17 Burusho+Lezgin @ 6.148676
18 Chechen+Pathan @ 6.152444
19 Chechen+Kalash @ 6.161303
20 GujaratiA+Kumyk @ 6.184081
21321 iterations.

Using 3 populations approximation:
1 50% Kalash +25% Balochi +25% North_Ossetian @ 4.040978
2 50% Kalash +25% Afghan_Uzbeki +25% Georgian @ 4.047966
3 50% Kalash +25% Balkar +25% Balochi @ 4.066488
4 50% Balochi +25% Kalash +25% North_Ossetian @ 4.070616
5 50% Balochi +25% Balkar +25% Kalash @ 4.101907
6 50% Kalash +25% Burusho +25% Georgian @ 4.103662
7 50% North_Ossetian +25% Kalash +25% Velamas @ 4.158732
8 50% Adygei +25% Kalash +25% Velamas @ 4.208915
9 50% Kalash +25% Balochi +25% Kumyk @ 4.232104
10 50% Kalash +25% Abkhasian +25% Afghan_Uzbeki @ 4.236385
11 50% Kalash +25% Georgian +25% Tadjik @ 4.244425
12 50% Kalash +25% Afghan_Tadjik +25% Georgian @ 4.289555
13 50% Balkar +25% Kalash +25% Velamas @ 4.289562
14 50% Balochi +25% Kalash +25% Kumyk @ 4.31676
15 50% Kalash +25% Abkhasian +25% Burusho @ 4.341414
16 50% Adygei +25% Brahmin_TN +25% Kalash @ 4.361319
17 50% Kalash +25% Abkhasian +25% Tadjik @ 4.391343
18 50% Kalash +25% Burusho +25% Turk_Trabzon @ 4.402696
19 50% North_Ossetian +25% Brahmin_TN +25% Kalash @ 4.406413
20 50% Kalash +25% Armenian +25% Burusho @ 4.454478
3962881 iterations.

Using 4 populations approximation:
1 Balochi+Kalash+Kalash+North_Ossetian @ 4.040978
2 Afghan_Uzbeki+Georgian+Kalash+Kalash @ 4.047966
3 Balkar+Balochi+Kalash+Kalash @ 4.066488
4 Balochi+Balochi+Kalash+North_Ossetian @ 4.070616
5 Balkar+Balochi+Balochi+Kalash @ 4.101907
6 Burusho+Georgian+Kalash+Kalash @ 4.103662
7 Adygei+Kalash+North_Ossetian+Velamas @ 4.110138
8 Kalash+North_Ossetian+North_Ossetian+Velamas @ 4.158732
9 Adygei+Balkar+Kalash+Velamas @ 4.169785
10 Adygei+Adygei+Kalash+Velamas @ 4.208915
11 Balochi+Kalash+North_Ossetian+Pathan @ 4.215849
12 Balkar+Kalash+North_Ossetian+Velamas @ 4.224765
13 Abkhasian+Brahmin_TN+Kalash+North_Ossetian @ 4.23024
14 Balochi+Kalash+Kalash+Kumyk @ 4.232104
15 Abkhasian+Afghan_Uzbeki+Kalash+Kalash @ 4.236385
16 Georgian+Kalash+Kalash+Tadjik @ 4.244425
17 Balkar+Balochi+Kalash+Pathan @ 4.247891
18 Abkhasian+Balkar+Brahmin_TN+Kalash @ 4.271003
19 Afghan_Tadjik+Georgian+Kalash+Kalash @ 4.289555
20 Balkar+Balkar+Kalash+Velamas @ 4.289562
21 Abkhasian+Balochi+Burusho+Kalash @ 4.307219
22 Balochi+Balochi+Kalash+Kumyk @ 4.31676
23 Adygei+Brahmin_TN+Kalash+North_Ossetian @ 4.323758
24 Abkhasian+Kalash+North_Ossetian+Velamas @ 4.335433
25 Abkhasian+Burusho+Kalash+Kalash @ 4.341414
26 Balochi+Burusho+Georgian+Kalash @ 4.344611
27 Abkhasian+GujaratiB+Kalash+North_Ossetian @ 4.354686
28 Chechen+Kalash+North_Ossetian+Velamas @ 4.355072
29 Brahmin_TN+Georgian+Kalash+North_Ossetian @ 4.359756
30 Adygei+Adygei+Brahmin_TN+Kalash @ 4.361319
31 Abkhasian+Balkar+Kalash+Velamas @ 4.366911
32 Adygei+Balkar+Brahmin_TN+Kalash @ 4.381165
33 Kalash+Lezgin+North_Ossetian+Velamas @ 4.381951
34 Abkhasian+Balkar+GujaratiB+Kalash @ 4.383349
35 Burusho+Georgian+Kalash+Pathan @ 4.387543
36 Abkhasian+Kalash+Kalash+Tadjik @ 4.391343
37 Balkar+Brahmin_TN+Georgian+Kalash @ 4.393343
38 Balkar+Chechen+Kalash+Velamas @ 4.398421
39 Burusho+Kalash+Kalash+Turk_Trabzon @ 4.402696
40 Brahmin_TN+Kalash+North_Ossetian+North_Ossetian @ 4.406413
57108943 iterations.




That was quick. Sukriya!

[Generalissimo]

why gujarati is more closer to us than a Punjabi on oracle?

The Punjabi Lahore sample has a lot of South Asian admixture, a lot more than GujaratiA.

[BalkanKiwi]

Czechs are quite high in many oracle results. In my case it's on top, whereas my Czech ancestry represents only 1.8% of my known ancestry. Unfortunately, there are no German samples. In my case Czech seems to replace (North)German. I don't know why .... Any thoughts?

Czech is my second population however I have no known Czech or German ancestry. I get a lot of German on other calculators so I suspect it's the equivalent maybe?

[Generalissimo]

Afghan Pashtuns and Utah Germans are now in the spreadsheet. But it might be useful to remove the extreme outliers from each group for any oracle type stuff.

[Longbowman]

^Yeah, the first Bosnian is obviously part Gypsy.

Oracle not working for me :(

EEF 0,523939
Central_Asian 0,259108
European 0,178994
Sub-Saharan 0,01266
Amerindian 0,012637
Siberian 0,00986
East_Asian 0,002783
Oceanian 0,00001
South_Asian 0,00001

[SwampThing27]

^Yeah, the first Bosnian is obviously part Gypsy.

Oracle not working for me :(

EEF 0,523939
Central_Asian 0,259108
European 0,178994
Sub-Saharan 0,01266
Amerindian 0,012637
Siberian 0,00986
East_Asian 0,002783
Oceanian 0,00001
South_Asian 0,00001

Did you try plugging your numbers into the spreadsheet with decimals instead of commas?

[randwulf]

My mom (1/2 Colonial Virginia English/Scottish/North and West German/French/Irish mix, 3/8 Colonial PA West and South German, 1/16 middle 1800s English immigrant to USA, 1/16 Vermont-born unknown middle 1800s):

K6

Yamnaya_related 0.359377
WHG_extra 0.047795
ENA 1E-005
Middle_Eastern 0.086189
Pre-Yamnaya 0.5015
Sub-Saharan 0.005129


K8

ANE 0.12934
South_Eurasian 0.005675
Near_Eastern 0.413579
East_Eurasian 1E-005
WHG 0.448452
Oceanian 1E-005
Pygmy 0.002924
Sub-Saharan 1E-005


K9

Oceanian 1E-005
Siberian 1E-005
Sub-Saharan 1E-005
East_Asian 1E-005
Central_Asian 0.150361
South_Asian 0.0199
Amerindian 1E-005
EEF 0.333863
European 0.495826

K9 Oracle:

[email protected] 3.15187066774639
[email protected] 6.0180524531924
[email protected] 6.21566993045601
[email protected] 6.29871633481901
[email protected] 7.08422112020792
[email protected] 7.11096091591706
[email protected] 7.66852894758832
[email protected] 7.75977197876329
[email protected] 8.54648621166033
[email protected] 8.68201437631988
[email protected] 9.17203161510049
[email protected] 9.57157772231471
[email protected] 10.6522610294716
[email protected] 11.3438927172995
[email protected] 11.8712921198106
[email protected] 12.1761557283077
[email protected] 13.0007770736983
[email protected] 13.3409789303503
[email protected] 13.5620499312385
[email protected] 14.4538635297434

[surbakhunWeesste]

Oracle using the updated spreadsheet.

[email protected] 8.38376313155375
[email protected] 8.95043215679184
[email protected] 10.3673780029897
[email protected] 14.7045336161553
[email protected] 14.739228326402
[email protected] 15.7675750942749
[email protected] 15.900579229109
[email protected] 17.5110124877347
[email protected] 17.5870177434607
[email protected] 18.8395289304497
[email protected] 23.098494164021
[email protected] 24.1675876782456
[email protected] 24.9660377482334
[email protected] 25.5276956420347
[email protected] 25.7255831708127
[email protected] 25.7681376971986
[email protected] 28.0332800246033
[email protected] 28.4146869550709
[email protected] 29.7972595531369
[email protected] 30.2951171907619
[email protected] 30.6888962524812

Mixed Mode
Thanks to Noel


Least-squares method.

Using 1 population approximation:
1 Afghan_Pashtun @ 8.549158
2 Brahui @ 9.01624
3 Balochi @ 10.372147
4 Kalash @ 14.684675
5 Tajik_Pomiri @ 14.865319
6 Pathan @ 15.828055
7 Tadjik @ 16.052636
8 Afghan_Uzbeki @ 17.652014
9 Afghan_Tadjik @ 17.736666
10 Burusho @ 18.944936
11 Lezgin @ 23.119637
12 Chechen @ 24.201623
13 Kumyk @ 25.017448
14 Adygei @ 25.556184
15 North_Ossetian @ 25.762994
16 Balkar @ 25.809018
17 Iranian @ 28.076273
18 Turkmen @ 28.543123
19 Abkhasian @ 29.790336
20 GujaratiA @ 30.339597
206 iterations.

Using 2 populations approximation:
1 Afghan_Pashtun+Brahui @ 6.402204
2 Balochi+Tajik_Pomiri @ 6.678817
3 Afghan_Pashtun+Balochi @ 6.70616
4 Brahui+Tajik_Pomiri @ 6.90073
5 Kalash+Kumyk @ 7.024658
6 Balochi+Tadjik @ 7.419435
7 Lezgin+Pathan @ 7.459736
8 Kalash+North_Ossetian @ 7.530901
9 Balkar+Kalash @ 7.53937
10 Iranian+Kalash @ 7.672983
11 Adygei+Kalash @ 7.677836
12 Burusho+Lezgin @ 7.750212
13 Kalash+Tadjik @ 7.93254
14 Afghan_Pashtun+Kalash @ 8.160688
15 Afghan_Uzbeki+Kalash @ 8.169509
16 Brahui+Tadjik @ 8.217538
17 Brahui+Kalash @ 8.345199
18 Chechen+Kalash @ 8.405373
19 Chechen+Pathan @ 8.449164
20 Abkhasian+GujaratiA @ 8.515109
21321 iterations.

Using 3 populations approximation:
1 50% Kalash +25% Abkhasian +25% Afghan_Tadjik @ 2.588696
2 50% Kalash +25% Afghan_Tadjik +25% Georgian @ 2.596027
3 50% Kalash +25% Abkhasian +25% Afghan_Uzbeki @ 2.606547
4 50% Kalash +25% Afghan_Uzbeki +25% Georgian @ 2.732609
5 50% Kalash +25% Afghan_Pashtun +25% Georgian @ 2.790689
6 50% Kalash +25% Abkhasian +25% Afghan_Pashtun @ 2.794559
7 50% Kalash +25% Balkar +25% Brahui @ 2.827152
8 50% Kalash +25% Brahui +25% North_Ossetian @ 2.837691
9 50% Kalash +25% Afghan_Pashtun +25% Kurdish @ 2.859077
10 50% Kalash +25% Brahui +25% Kumyk @ 3.006396
11 50% Kalash +25% Balkar +25% Balochi @ 3.010658
12 50% Balochi +25% Balkar +25% Kalash @ 3.012342
13 50% Balochi +25% Kalash +25% North_Ossetian @ 3.015742
14 50% Kalash +25% Balochi +25% North_Ossetian @ 3.028993
15 50% Kalash +25% Burusho +25% Georgian @ 3.152125
16 50% Kalash +25% Afghan_Pashtun +25% Iranian @ 3.187833
17 50% Kalash +25% Adygei +25% Brahui @ 3.21308
18 50% Kalash +25% Balochi +25% Kumyk @ 3.255653
19 50% Balochi +25% Chechen +25% Kalash @ 3.315838
20 50% Balochi +25% Adygei +25% Kalash @ 3.32776
2554129 iterations.

Using 4 populations approximation:
1 Abkhasian+Afghan_Tadjik+Kalash+Kalash @ 2.588696
2 Afghan_Tadjik+Georgian+Kalash+Kalash @ 2.596027
3 Abkhasian+Afghan_Uzbeki+Kalash+Kalash @ 2.606547
4 Afghan_Uzbeki+Georgian+Kalash+Kalash @ 2.732609
5 Afghan_Pashtun+Georgian+Kalash+Kalash @ 2.790689
6 Abkhasian+Afghan_Pashtun+Kalash+Kalash @ 2.794559
7 Balkar+Brahui+Kalash+Kalash @ 2.827152
8 Brahui+Kalash+Kalash+North_Ossetian @ 2.837691
9 Afghan_Pashtun+Kalash+Kalash+Kurdish @ 2.859077
10 Abkhasian+Afghan_Pashtun+Kalash+Pathan @ 3.00137
11 Brahui+Kalash+Kalash+Kumyk @ 3.006396
12 Balkar+Balochi+Kalash+Kalash @ 3.010658
13 Balkar+Balochi+Balochi+Kalash @ 3.012342
14 Balochi+Balochi+Kalash+North_Ossetian @ 3.015742
15 Balochi+Kalash+Kalash+North_Ossetian @ 3.028993
16 Burusho+Georgian+Kalash+Kalash @ 3.152125
17 Adygei+Afghan_Pashtun+Balochi+Kalash @ 3.166004
18 Afghan_Pashtun+Iranian+Kalash+Kalash @ 3.187833
19 Afghan_Pashtun+Balochi+Kalash+North_Ossetian @ 3.196032
20 Adygei+Brahui+Kalash+Kalash @ 3.21308
21 Afghan_Pashtun+Balochi+Kalash+Lezgin @ 3.246575
22 Afghan_Pashtun+Balkar+Balochi+Kalash @ 3.251667
23 Balochi+Kalash+Kalash+Kumyk @ 3.255653
24 Abkhasian+Afghan_Pashtun+Burusho+Kalash @ 3.259381
25 Balochi+Brahui+Kalash+North_Ossetian @ 3.290985
26 Balkar+Balochi+Brahui+Kalash @ 3.295622
27 Balochi+Balochi+Chechen+Kalash @ 3.315838
28 Abkhasian+Brahui+Burusho+Kalash @ 3.316509
29 Adygei+Balochi+Balochi+Kalash @ 3.32776
30 Afghan_Pashtun+Burusho+Georgian+Kalash @ 3.32779
31 Abkhasian+Balochi+Burusho+Kalash @ 3.336072
32 Abkhasian+Afghan_Pashtun+Balochi+Kalash @ 3.389356
33 Afghan_Pashtun+Georgian+Kalash+Pathan @ 3.391377
34 Balochi+Brahui+Kalash+Lezgin @ 3.401329
35 Adygei+Balochi+Kalash+Kalash @ 3.415521
36 Balochi+Brahui+Chechen+Kalash @ 3.419978
37 Balochi+Balochi+Kalash+Lezgin @ 3.422323
38 Afghan_Pashtun+Balochi+Chechen+Kalash @ 3.484942
39 Adygei+Balochi+Brahui+Kalash @ 3.548278
40 Balochi+Balochi+Kalash+Kumyk @ 3.569
13130588 iterations.


Gaussian method.
Noise dispersion set to 0.584552

Using 1 population approximation:
1 Afghan_Pashtun @ 6.403599
2 Balochi @ 7.966524
3 Tajik_Pomiri @ 8.417629
4 Pathan @ 8.444321
5 Brahui @ 9.170588
6 Tadjik @ 9.714776
7 Afghan_Uzbeki @ 10.069627
8 Afghan_Tadjik @ 10.38787
9 Burusho @ 10.894179
10 Iranian @ 14.338449
11 Turkmen @ 15.108975
12 GujaratiA @ 15.211172
13 Kurdish @ 16.186658
14 Uzbek @ 16.416393
15 Afghan_Turkmen @ 16.754677
16 Uzbeki @ 17.495425
17 Brahmin_UP @ 18.84692
18 Brahmin_TN @ 19.478395
19 GujaratiB @ 19.563944
20 Kshatriya @ 19.954498
206 iterations.

Using 2 populations approximation:
1 Afghan_Pashtun+Balochi @ 5.079171
2 Kalash+Kumyk @ 5.252422
3 Kalash+North_Ossetian @ 5.386519
4 Adygei+Kalash @ 5.394973
5 Balkar+Kalash @ 5.46351
6 GujaratiA+North_Ossetian @ 5.587334
7 Adygei+GujaratiA @ 5.635504
8 Adygei+Pathan @ 5.678588
9 Balkar+GujaratiA @ 5.685926
10 North_Ossetian+Pathan @ 5.731406
11 Balkar+Pathan @ 5.81852
12 Balochi+Tajik_Pomiri @ 5.835902
13 GujaratiB+North_Ossetian @ 5.94038
14 Balochi+Tadjik @ 5.945503
15 Adygei+GujaratiB @ 5.968332
16 Kumyk+Pathan @ 5.970778
17 Balkar+GujaratiB @ 6.033144
18 Burusho+Lezgin @ 6.148568
19 Chechen+Pathan @ 6.155505
20 Chechen+Kalash @ 6.164884
21321 iterations.

Using 3 populations approximation:
1 50% Kalash +25% Afghan_Pashtun +25% Georgian @ 3.911582
2 50% Kalash +25% Abkhasian +25% Afghan_Pashtun @ 3.936978
3 50% Kalash +25% Balochi +25% North_Ossetian @ 4.039635
4 50% Kalash +25% Afghan_Uzbeki +25% Georgian @ 4.05053
5 50% Kalash +25% Balkar +25% Balochi @ 4.064034
6 50% Balochi +25% Kalash +25% North_Ossetian @ 4.066578
7 50% Balochi +25% Balkar +25% Kalash @ 4.09644
8 50% Kalash +25% Burusho +25% Georgian @ 4.106424
9 50% North_Ossetian +25% Kalash +25% Velamas @ 4.165707
10 50% Adygei +25% Kalash +25% Velamas @ 4.213226
11 50% Kalash +25% Balochi +25% Kumyk @ 4.227998
12 50% Kalash +25% Abkhasian +25% Afghan_Uzbeki @ 4.23675
13 50% Kalash +25% Afghan_Pashtun +25% Kurdish @ 4.242677
14 50% Kalash +25% Georgian +25% Tadjik @ 4.243714
15 50% Kalash +25% Afghan_Tadjik +25% Georgian @ 4.286921
16 50% Balkar +25% Kalash +25% Velamas @ 4.293402
17 50% Balochi +25% Kalash +25% Kumyk @ 4.310774
18 50% Kalash +25% Abkhasian +25% Burusho @ 4.340018
19 50% Adygei +25% Brahmin_TN +25% Kalash @ 4.364506
20 50% Kalash +25% Afghan_Pashtun +25% Armenian @ 4.387637
4002914 iterations.

Using 4 populations approximation:
1 Afghan_Pashtun+Georgian+Kalash+Kalash @ 3.911582
2 Abkhasian+Afghan_Pashtun+Kalash+Kalash @ 3.936978
3 Balochi+Kalash+Kalash+North_Ossetian @ 4.039635
4 Afghan_Uzbeki+Georgian+Kalash+Kalash @ 4.05053
5 Balkar+Balochi+Kalash+Kalash @ 4.064034
6 Balochi+Balochi+Kalash+North_Ossetian @ 4.066578
7 Abkhasian+Afghan_Pashtun+Kalash+Pathan @ 4.094958
8 Balkar+Balochi+Balochi+Kalash @ 4.09644
9 Burusho+Georgian+Kalash+Kalash @ 4.106424
10 Adygei+Kalash+North_Ossetian+Velamas @ 4.116189
11 Afghan_Pashtun+Georgian+Kalash+Pathan @ 4.158948
12 Kalash+North_Ossetian+North_Ossetian+Velamas @ 4.165707
13 Adygei+Balkar+Kalash+Velamas @ 4.174133
14 Adygei+Afghan_Pashtun+Balochi+Kalash @ 4.179953
15 Abkhasian+Afghan_Pashtun+Balochi+Kalash @ 4.187103
16 Adygei+Adygei+Kalash+Velamas @ 4.213226
17 Balochi+Kalash+North_Ossetian+Pathan @ 4.214007
18 Balochi+Kalash+Kalash+Kumyk @ 4.227998
19 Afghan_Pashtun+Balochi+Kalash+North_Ossetian @ 4.228839
20 Balkar+Kalash+North_Ossetian+Velamas @ 4.230156
21 Abkhasian+Brahmin_TN+Kalash+North_Ossetian @ 4.231345
22 Abkhasian+Afghan_Uzbeki+Kalash+Kalash @ 4.23675
23 Afghan_Pashtun+Kalash+Kalash+Kurdish @ 4.242677
24 Georgian+Kalash+Kalash+Tadjik @ 4.243714
25 Balkar+Balochi+Kalash+Pathan @ 4.244612
26 Abkhasian+Balkar+Brahmin_TN+Kalash @ 4.270909
27 Afghan_Pashtun+Balkar+Balochi+Kalash @ 4.285932
28 Afghan_Tadjik+Georgian+Kalash+Kalash @ 4.286921
29 Balkar+Balkar+Kalash+Velamas @ 4.293402
30 Abkhasian+Balochi+Burusho+Kalash @ 4.302686
31 Balochi+Balochi+Kalash+Kumyk @ 4.310774
32 Adygei+Brahmin_TN+Kalash+North_Ossetian @ 4.328865
33 Abkhasian+Kalash+North_Ossetian+Velamas @ 4.335822
34 Abkhasian+Burusho+Kalash+Kalash @ 4.340018
35 Balochi+Burusho+Georgian+Kalash @ 4.343047
36 Abkhasian+GujaratiB+Kalash+North_Ossetian @ 4.353938
37 Chechen+Kalash+North_Ossetian+Velamas @ 4.359967
38 Brahmin_TN+Georgian+Kalash+North_Ossetian @ 4.364005
39 Adygei+Adygei+Brahmin_TN+Kalash @ 4.364506
40 Abkhasian+Balkar+Kalash+Velamas @ 4.366251
59662913 iterations.

[Kurd]

Updated K9 Oracle & Mixed Mode courtesy Noel:

http://i.imgur.com/e7781W1.jpg
http://i.imgur.com/Jmm5FGm.jpg

[Longbowman]

Did you try plugging your numbers into the spreadsheet with decimals instead of commas?

Cheers, mate.


1 [email protected] 2.14897834957554
2 [email protected] 2.68851747191645
3 [email protected] 2.80536391327728
4 [email protected] 3.99726072638344
5 [email protected] 4.67938585668061
6 [email protected] 5.83859648682262
7 [email protected] 6.50383621269823
8 [email protected] 6.94873462945773
9 [email protected] 9.63801266102376
10 [email protected] 9.71279098056898
11 [email protected] 9.81686137539641
12 [email protected] 13.2019867729808
13 [email protected] 13.4036866969211
14 [email protected] 13.4863490673911
15 [email protected] 14.1575738359257
16 [email protected] 14.4026654847192
17 [email protected] 16.7795084199982
18 [email protected] 17.8242650085188
19 [email protected] 18.0468927888224
20 [email protected] 18.6887964999514

A little too northern-shifted, but they all say that.

[Kurd]

Oracle using the updated spreadsheet.

[email protected] 8.38376313155375
[email protected] 8.95043215679184
[email protected] 10.3673780029897
[email protected] 14.7045336161553
[email protected] 14.739228326402
[email protected] 15.7675750942749
[email protected] 15.900579229109
[email protected] 17.5110124877347
[email protected] 17.5870177434607
[email protected] 18.8395289304497
[email protected] 23.098494164021
[email protected] 24.1675876782456
[email protected] 24.9660377482334
[email protected] 25.5276956420347
[email protected] 25.7255831708127
[email protected] 25.7681376971986
[email protected] 28.0332800246033
[email protected] 28.4146869550709
[email protected] 29.7972595531369
[email protected] 30.2951171907619
[email protected] 30.6888962524812

Mixed Mode
Thanks to Noel


Least-squares method.

Using 1 population approximation:
1 Afghan_Pashtun @ 8.549158
2 Brahui @ 9.01624
3 Balochi @ 10.372147
4 Kalash @ 14.684675
5 Tajik_Pomiri @ 14.865319
6 Pathan @ 15.828055
7 Tadjik @ 16.052636
8 Afghan_Uzbeki @ 17.652014
9 Afghan_Tadjik @ 17.736666
10 Burusho @ 18.944936
11 Lezgin @ 23.119637
12 Chechen @ 24.201623
13 Kumyk @ 25.017448
14 Adygei @ 25.556184
15 North_Ossetian @ 25.762994
16 Balkar @ 25.809018
17 Iranian @ 28.076273
18 Turkmen @ 28.543123
19 Abkhasian @ 29.790336
20 GujaratiA @ 30.339597
206 iterations.

Using 2 populations approximation:
1 Afghan_Pashtun+Brahui @ 6.402204
2 Balochi+Tajik_Pomiri @ 6.678817
3 Afghan_Pashtun+Balochi @ 6.70616
4 Brahui+Tajik_Pomiri @ 6.90073
5 Kalash+Kumyk @ 7.024658
6 Balochi+Tadjik @ 7.419435
7 Lezgin+Pathan @ 7.459736
8 Kalash+North_Ossetian @ 7.530901
9 Balkar+Kalash @ 7.53937
10 Iranian+Kalash @ 7.672983
11 Adygei+Kalash @ 7.677836
12 Burusho+Lezgin @ 7.750212
13 Kalash+Tadjik @ 7.93254
14 Afghan_Pashtun+Kalash @ 8.160688
15 Afghan_Uzbeki+Kalash @ 8.169509
16 Brahui+Tadjik @ 8.217538
17 Brahui+Kalash @ 8.345199
18 Chechen+Kalash @ 8.405373
19 Chechen+Pathan @ 8.449164
20 Abkhasian+GujaratiA @ 8.515109
21321 iterations.

Using 3 populations approximation:
1 50% Kalash +25% Abkhasian +25% Afghan_Tadjik @ 2.588696
2 50% Kalash +25% Afghan_Tadjik +25% Georgian @ 2.596027
3 50% Kalash +25% Abkhasian +25% Afghan_Uzbeki @ 2.606547
4 50% Kalash +25% Afghan_Uzbeki +25% Georgian @ 2.732609
5 50% Kalash +25% Afghan_Pashtun +25% Georgian @ 2.790689
6 50% Kalash +25% Abkhasian +25% Afghan_Pashtun @ 2.794559
7 50% Kalash +25% Balkar +25% Brahui @ 2.827152
8 50% Kalash +25% Brahui +25% North_Ossetian @ 2.837691
9 50% Kalash +25% Afghan_Pashtun +25% Kurdish @ 2.859077
10 50% Kalash +25% Brahui +25% Kumyk @ 3.006396
11 50% Kalash +25% Balkar +25% Balochi @ 3.010658
12 50% Balochi +25% Balkar +25% Kalash @ 3.012342
13 50% Balochi +25% Kalash +25% North_Ossetian @ 3.015742
14 50% Kalash +25% Balochi +25% North_Ossetian @ 3.028993
15 50% Kalash +25% Burusho +25% Georgian @ 3.152125
16 50% Kalash +25% Afghan_Pashtun +25% Iranian @ 3.187833
17 50% Kalash +25% Adygei +25% Brahui @ 3.21308
18 50% Kalash +25% Balochi +25% Kumyk @ 3.255653
19 50% Balochi +25% Chechen +25% Kalash @ 3.315838
20 50% Balochi +25% Adygei +25% Kalash @ 3.32776
2554129 iterations.

Using 4 populations approximation:
1 Abkhasian+Afghan_Tadjik+Kalash+Kalash @ 2.588696
2 Afghan_Tadjik+Georgian+Kalash+Kalash @ 2.596027
3 Abkhasian+Afghan_Uzbeki+Kalash+Kalash @ 2.606547
4 Afghan_Uzbeki+Georgian+Kalash+Kalash @ 2.732609
5 Afghan_Pashtun+Georgian+Kalash+Kalash @ 2.790689
6 Abkhasian+Afghan_Pashtun+Kalash+Kalash @ 2.794559
7 Balkar+Brahui+Kalash+Kalash @ 2.827152
8 Brahui+Kalash+Kalash+North_Ossetian @ 2.837691
9 Afghan_Pashtun+Kalash+Kalash+Kurdish @ 2.859077
10 Abkhasian+Afghan_Pashtun+Kalash+Pathan @ 3.00137
11 Brahui+Kalash+Kalash+Kumyk @ 3.006396
12 Balkar+Balochi+Kalash+Kalash @ 3.010658
13 Balkar+Balochi+Balochi+Kalash @ 3.012342
14 Balochi+Balochi+Kalash+North_Ossetian @ 3.015742
15 Balochi+Kalash+Kalash+North_Ossetian @ 3.028993
16 Burusho+Georgian+Kalash+Kalash @ 3.152125
17 Adygei+Afghan_Pashtun+Balochi+Kalash @ 3.166004
18 Afghan_Pashtun+Iranian+Kalash+Kalash @ 3.187833
19 Afghan_Pashtun+Balochi+Kalash+North_Ossetian @ 3.196032
20 Adygei+Brahui+Kalash+Kalash @ 3.21308
21 Afghan_Pashtun+Balochi+Kalash+Lezgin @ 3.246575
22 Afghan_Pashtun+Balkar+Balochi+Kalash @ 3.251667
23 Balochi+Kalash+Kalash+Kumyk @ 3.255653
24 Abkhasian+Afghan_Pashtun+Burusho+Kalash @ 3.259381
25 Balochi+Brahui+Kalash+North_Ossetian @ 3.290985
26 Balkar+Balochi+Brahui+Kalash @ 3.295622
27 Balochi+Balochi+Chechen+Kalash @ 3.315838
28 Abkhasian+Brahui+Burusho+Kalash @ 3.316509
29 Adygei+Balochi+Balochi+Kalash @ 3.32776
30 Afghan_Pashtun+Burusho+Georgian+Kalash @ 3.32779
31 Abkhasian+Balochi+Burusho+Kalash @ 3.336072
32 Abkhasian+Afghan_Pashtun+Balochi+Kalash @ 3.389356
33 Afghan_Pashtun+Georgian+Kalash+Pathan @ 3.391377
34 Balochi+Brahui+Kalash+Lezgin @ 3.401329
35 Adygei+Balochi+Kalash+Kalash @ 3.415521
36 Balochi+Brahui+Chechen+Kalash @ 3.419978
37 Balochi+Balochi+Kalash+Lezgin @ 3.422323
38 Afghan_Pashtun+Balochi+Chechen+Kalash @ 3.484942
39 Adygei+Balochi+Brahui+Kalash @ 3.548278
40 Balochi+Balochi+Kalash+Kumyk @ 3.569
13130588 iterations.


Gaussian method.
Noise dispersion set to 0.584552

Using 1 population approximation:
1 Afghan_Pashtun @ 6.403599
2 Balochi @ 7.966524
3 Tajik_Pomiri @ 8.417629
4 Pathan @ 8.444321
5 Brahui @ 9.170588
6 Tadjik @ 9.714776
7 Afghan_Uzbeki @ 10.069627
8 Afghan_Tadjik @ 10.38787
9 Burusho @ 10.894179
10 Iranian @ 14.338449
11 Turkmen @ 15.108975
12 GujaratiA @ 15.211172
13 Kurdish @ 16.186658
14 Uzbek @ 16.416393
15 Afghan_Turkmen @ 16.754677
16 Uzbeki @ 17.495425
17 Brahmin_UP @ 18.84692
18 Brahmin_TN @ 19.478395
19 GujaratiB @ 19.563944
20 Kshatriya @ 19.954498
206 iterations.

Using 2 populations approximation:
1 Afghan_Pashtun+Balochi @ 5.079171
2 Kalash+Kumyk @ 5.252422
3 Kalash+North_Ossetian @ 5.386519
4 Adygei+Kalash @ 5.394973
5 Balkar+Kalash @ 5.46351
6 GujaratiA+North_Ossetian @ 5.587334
7 Adygei+GujaratiA @ 5.635504
8 Adygei+Pathan @ 5.678588
9 Balkar+GujaratiA @ 5.685926
10 North_Ossetian+Pathan @ 5.731406
11 Balkar+Pathan @ 5.81852
12 Balochi+Tajik_Pomiri @ 5.835902
13 GujaratiB+North_Ossetian @ 5.94038
14 Balochi+Tadjik @ 5.945503
15 Adygei+GujaratiB @ 5.968332
16 Kumyk+Pathan @ 5.970778
17 Balkar+GujaratiB @ 6.033144
18 Burusho+Lezgin @ 6.148568
19 Chechen+Pathan @ 6.155505
20 Chechen+Kalash @ 6.164884
21321 iterations.

Using 3 populations approximation:
1 50% Kalash +25% Afghan_Pashtun +25% Georgian @ 3.911582
2 50% Kalash +25% Abkhasian +25% Afghan_Pashtun @ 3.936978
3 50% Kalash +25% Balochi +25% North_Ossetian @ 4.039635
4 50% Kalash +25% Afghan_Uzbeki +25% Georgian @ 4.05053
5 50% Kalash +25% Balkar +25% Balochi @ 4.064034
6 50% Balochi +25% Kalash +25% North_Ossetian @ 4.066578
7 50% Balochi +25% Balkar +25% Kalash @ 4.09644
8 50% Kalash +25% Burusho +25% Georgian @ 4.106424
9 50% North_Ossetian +25% Kalash +25% Velamas @ 4.165707
10 50% Adygei +25% Kalash +25% Velamas @ 4.213226
11 50% Kalash +25% Balochi +25% Kumyk @ 4.227998
12 50% Kalash +25% Abkhasian +25% Afghan_Uzbeki @ 4.23675
13 50% Kalash +25% Afghan_Pashtun +25% Kurdish @ 4.242677
14 50% Kalash +25% Georgian +25% Tadjik @ 4.243714
15 50% Kalash +25% Afghan_Tadjik +25% Georgian @ 4.286921
16 50% Balkar +25% Kalash +25% Velamas @ 4.293402
17 50% Balochi +25% Kalash +25% Kumyk @ 4.310774
18 50% Kalash +25% Abkhasian +25% Burusho @ 4.340018
19 50% Adygei +25% Brahmin_TN +25% Kalash @ 4.364506
20 50% Kalash +25% Afghan_Pashtun +25% Armenian @ 4.387637
4002914 iterations.

Using 4 populations approximation:
1 Afghan_Pashtun+Georgian+Kalash+Kalash @ 3.911582
2 Abkhasian+Afghan_Pashtun+Kalash+Kalash @ 3.936978
3 Balochi+Kalash+Kalash+North_Ossetian @ 4.039635
4 Afghan_Uzbeki+Georgian+Kalash+Kalash @ 4.05053
5 Balkar+Balochi+Kalash+Kalash @ 4.064034
6 Balochi+Balochi+Kalash+North_Ossetian @ 4.066578
7 Abkhasian+Afghan_Pashtun+Kalash+Pathan @ 4.094958
8 Balkar+Balochi+Balochi+Kalash @ 4.09644
9 Burusho+Georgian+Kalash+Kalash @ 4.106424
10 Adygei+Kalash+North_Ossetian+Velamas @ 4.116189
11 Afghan_Pashtun+Georgian+Kalash+Pathan @ 4.158948
12 Kalash+North_Ossetian+North_Ossetian+Velamas @ 4.165707
13 Adygei+Balkar+Kalash+Velamas @ 4.174133
14 Adygei+Afghan_Pashtun+Balochi+Kalash @ 4.179953
15 Abkhasian+Afghan_Pashtun+Balochi+Kalash @ 4.187103
16 Adygei+Adygei+Kalash+Velamas @ 4.213226
17 Balochi+Kalash+North_Ossetian+Pathan @ 4.214007
18 Balochi+Kalash+Kalash+Kumyk @ 4.227998
19 Afghan_Pashtun+Balochi+Kalash+North_Ossetian @ 4.228839
20 Balkar+Kalash+North_Ossetian+Velamas @ 4.230156
21 Abkhasian+Brahmin_TN+Kalash+North_Ossetian @ 4.231345
22 Abkhasian+Afghan_Uzbeki+Kalash+Kalash @ 4.23675
23 Afghan_Pashtun+Kalash+Kalash+Kurdish @ 4.242677
24 Georgian+Kalash+Kalash+Tadjik @ 4.243714
25 Balkar+Balochi+Kalash+Pathan @ 4.244612
26 Abkhasian+Balkar+Brahmin_TN+Kalash @ 4.270909
27 Afghan_Pashtun+Balkar+Balochi+Kalash @ 4.285932
28 Afghan_Tadjik+Georgian+Kalash+Kalash @ 4.286921
29 Balkar+Balkar+Kalash+Velamas @ 4.293402
30 Abkhasian+Balochi+Burusho+Kalash @ 4.302686
31 Balochi+Balochi+Kalash+Kumyk @ 4.310774
32 Adygei+Brahmin_TN+Kalash+North_Ossetian @ 4.328865
33 Abkhasian+Kalash+North_Ossetian+Velamas @ 4.335822
34 Abkhasian+Burusho+Kalash+Kalash @ 4.340018
35 Balochi+Burusho+Georgian+Kalash @ 4.343047
36 Abkhasian+GujaratiB+Kalash+North_Ossetian @ 4.353938
37 Chechen+Kalash+North_Ossetian+Velamas @ 4.359967
38 Brahmin_TN+Georgian+Kalash+North_Ossetian @ 4.364005
39 Adygei+Adygei+Brahmin_TN+Kalash @ 4.364506
40 Abkhasian+Balkar+Kalash+Velamas @ 4.366251
59662913 iterations.


It is interesting that my results show smaller distance (larger overlap) with Afghan Tajik & Afghan Uzbek than yours, my 15.3 & 15.4 vs your 17.5, 17.6, yet, your shows slightly smaller distance to Brahui & Baloch, your 9 & 10.4 vs my 10.6 & 12.7

EDIT: Disregard, I just noticed that I was comparing your results using the Least Squares Method vs. my results using the Gaussian method.:)

[ZephyrousMandaru]

After issues with having to format the text document and adding the Iraqi Mandaeans and with the help of Noel, I now have a functional Oracle-4.



Least-squares method.

Using 1 population approximation:
1 Assyrian @ 2.947144
2 Iranian_Jew @ 4.15288
3 Iraqi_Mandaean @ 4.385589
4 Iranian_Jewish @ 4.801356
5 Iraqi_Jewish @ 5.243023
6 Iraqi_Jew @ 5.494848
7 Armenian @ 5.93881
8 Lebanese_Muslim @ 12.87993
9 Syrian @ 13.238686
10 Druze @ 13.723343
11 Kurdish @ 13.786179
12 Lebanese_Christian @ 14.370197
13 Lebanese @ 14.606291
14 Jordanian @ 16.495477
15 Iranian @ 16.598035
16 Cyprian @ 16.929178
17 Turkish @ 16.941466
18 Cypriot @ 17.138198
19 Palestinian @ 19.18136
20 Georgian @ 19.444791
207 iterations.

Using 2 populations approximation:
1 Armenian+Iraqi_Jew @ 2.725844
2 Armenian+Iraqi_Jewish @ 2.807583
3 Assyrian+Assyrian @ 2.947144
4 Assyrian+Iranian_Jew @ 3.373131
5 Armenian+Iranian_Jew @ 3.501549
6 Assyrian+Iraqi_Mandaean @ 3.51031
7 Assyrian+Iranian_Jewish @ 3.525599
8 Iranian_Jewish+Iraqi_Jew @ 3.569161
9 Iranian_Jewish+Iraqi_Jewish @ 3.574618
10 Armenian+Iraqi_Mandaean @ 3.614897
11 Assyrian+Iraqi_Jewish @ 3.723666
12 Armenian+Assyrian @ 3.742577
13 Assyrian+Iraqi_Jew @ 3.788766
14 Georgian+Samaritan @ 3.847538
15 Iranian_Jew+Iranian_Jewish @ 4.054256
16 Iranian_Jewish+Iraqi_Mandaean @ 4.135271
17 Iranian_Jew+Iranian_Jew @ 4.15288
18 Iranian_Jew+Iraqi_Mandaean @ 4.230983
19 Georgian+Lebanese_Christian @ 4.316668
20 Abkhasian+Samaritan @ 4.375847
21528 iterations.

Using 3 populations approximation:
1 50% Iraqi_Jew +25% Georgian +25% Iraqi_Jew @ 2.220247
2 50% Iraqi_Jew +25% Georgian +25% Iraqi_Jewish @ 2.273438
3 50% Iraqi_Jewish +25% Georgian +25% Iraqi_Jew @ 2.342308
4 50% Iraqi_Jewish +25% Georgian +25% Iraqi_Jewish @ 2.425522
5 50% Armenian +25% Iraqi_Jew +25% Iraqi_Jew @ 2.725844
6 50% Iraqi_Jew +25% Georgian +25% Lebanese_Christian @ 2.734637
7 50% Iraqi_Jewish +25% Georgian +25% Lebanese_Christian @ 2.737698
8 50% Armenian +25% Iraqi_Jew +25% Iraqi_Jewish @ 2.759881
9 50% Iranian_Jew +25% Georgian +25% Lebanese_Christian @ 2.799328
10 50% Assyrian +25% Armenian +25% Iraqi_Jew @ 2.802769
11 50% Armenian +25% Iraqi_Jewish +25% Iraqi_Jewish @ 2.807583
12 50% Iraqi_Jew +25% Georgian +25% Iranian_Jew @ 2.826077
13 50% Assyrian +25% Armenian +25% Iraqi_Jewish @ 2.839379
14 50% Iraqi_Jew +25% Abkhasian +25% Iraqi_Jew @ 2.866824
15 50% Iraqi_Jew +25% Georgian +25% Iraqi_Mandaean @ 2.870038
16 50% Iraqi_Jew +25% Armenian +25% Iranian_Jewish @ 2.944544
17 50% Iraqi_Jew +25% Abkhasian +25% Iraqi_Jewish @ 2.957617
18 50% Iraqi_Mandaean +25% Georgian +25% Lebanese_Christian @ 2.963329
19 50% Iraqi_Jew +25% Abkhasian +25% Lebanese_Christian @ 2.97087
20 50% Iraqi_Jewish +25% Armenian +25% Assyrian @ 2.980174
653083 iterations.

Using 4 populations approximation:
1 Georgian+Iraqi_Jew+Iraqi_Jew+Iraqi_Jew @ 2.220247
2 Georgian+Iraqi_Jew+Iraqi_Jew+Iraqi_Jewish @ 2.273438
3 Georgian+Iraqi_Jew+Iraqi_Jewish+Iraqi_Jewish @ 2.342308
4 Georgian+Iraqi_Jewish+Iraqi_Jewish+Iraqi_Jewish @ 2.425522
5 Georgian+Iranian_Jew+Iraqi_Jew+Lebanese_Christian @ 2.597687
6 Georgian+Iranian_Jew+Iraqi_Jewish+Lebanese_Christi an @ 2.625452
7 Assyrian+Georgian+Iraqi_Jew+Lebanese_Christian @ 2.671273
8 Georgian+Iraqi_Jew+Iraqi_Mandaean+Lebanese_Christi an @ 2.68125
9 Assyrian+Georgian+Iraqi_Jewish+Lebanese_Christian @ 2.712898
10 Georgian+Iraqi_Jewish+Iraqi_Mandaean+Lebanese_Chri stian @ 2.71588
11 Armenian+Armenian+Iraqi_Jew+Iraqi_Jew @ 2.725844
12 Georgian+Iraqi_Jew+Iraqi_Jewish+Lebanese_Christian @ 2.728953
13 Georgian+Iraqi_Jew+Iraqi_Jew+Lebanese_Christian @ 2.734637
14 Georgian+Iraqi_Jewish+Iraqi_Jewish+Lebanese_Christ ian @ 2.737698
15 Armenian+Armenian+Iraqi_Jew+Iraqi_Jewish @ 2.759881
16 Georgian+Iranian_Jewish+Iraqi_Jew+Lebanese_Christi an @ 2.789074
17 Georgian+Iranian_Jew+Iranian_Jew+Lebanese_Christia n @ 2.799328
18 Armenian+Assyrian+Assyrian+Iraqi_Jew @ 2.802769
19 Armenian+Armenian+Iraqi_Jewish+Iraqi_Jewish @ 2.807583
20 Georgian+Iranian_Jew+Iraqi_Jew+Iraqi_Jew @ 2.826077
21 Armenian+Assyrian+Assyrian+Iraqi_Jewish @ 2.839379
22 Georgian+Iranian_Jewish+Iraqi_Jewish+Lebanese_Chri stian @ 2.852203
23 Assyrian+Georgian+Iranian_Jew+Lebanese_Christian @ 2.861622
24 Abkhasian+Iraqi_Jew+Iraqi_Jew+Iraqi_Jew @ 2.866824
25 Georgian+Iranian_Jew+Iraqi_Mandaean+Lebanese_Chris tian @ 2.86777
26 Georgian+Iraqi_Jew+Iraqi_Jew+Iraqi_Mandaean @ 2.870038
27 Georgian+Iranian_Jew+Iraqi_Jew+Iraqi_Jewish @ 2.898588
28 Armenian+Assyrian+Iranian_Jew+Iraqi_Jew @ 2.90758
29 Armenian+Assyrian+Iranian_Jew+Iraqi_Jewish @ 2.929416
30 Assyrian+Georgian+Iraqi_Mandaean+Lebanese_Christia n @ 2.940938
31 Armenian+Iranian_Jewish+Iraqi_Jew+Iraqi_Jew @ 2.944544
32 Assyrian+Assyrian+Assyrian+Assyrian @ 2.947144
33 Georgian+Iraqi_Jew+Iraqi_Jewish+Iraqi_Mandaean @ 2.948577
34 Abkhasian+Iraqi_Jew+Iraqi_Jew+Iraqi_Jewish @ 2.957617
35 Armenian+Iranian_Jewish+Iraqi_Jew+Iraqi_Jewish @ 2.958669
36 Assyrian+Georgian+Iranian_Jewish+Samaritan @ 2.961141
37 Georgian+Iraqi_Mandaean+Iraqi_Mandaean+Lebanese_Ch ristian @ 2.963329
38 Abkhasian+Iraqi_Jew+Iraqi_Jew+Lebanese_Christian @ 2.97087
39 Armenian+Assyrian+Iraqi_Jew+Iraqi_Jewish @ 2.975096
40 Armenian+Assyrian+Iraqi_Jew+Iraqi_Mandaean @ 2.976631
302385 iterations.


Gaussian method.
Noise dispersion set to 0.584552

Using 1 population approximation:
1 Iraqi_Jew @ 3.554062
2 Iraqi_Jewish @ 3.860179
3 Iranian_Jew @ 3.993739
4 Assyrian @ 4.232335
5 Iraqi_Mandaean @ 4.572307
6 Armenian @ 4.638497
7 Iranian_Jewish @ 4.699718
8 Lebanese_Christian @ 5.676041
9 Druze @ 6.190365
10 Lebanese_Muslim @ 6.901805
11 Kurdish @ 6.974348
12 Cyprian @ 6.995593
13 Cypriot @ 7.030627
14 Samaritan @ 7.054385
15 Syrian @ 7.118046
16 Georgian @ 7.256729
17 Lebanese @ 7.35003
18 Jordanian @ 7.440209
19 Palestinian @ 7.820623
20 Abkhasian @ 7.977007
207 iterations.

Using 2 populations approximation:
1 Iraqi_Jew+Iraqi_Jew @ 3.554062
2 Iraqi_Jew+Iraqi_Jewish @ 3.695507
3 Iranian_Jew+Iraqi_Jew @ 3.743942
4 Iranian_Jew+Iraqi_Jewish @ 3.855893
5 Iraqi_Jewish+Iraqi_Jewish @ 3.860179
6 Iranian_Jew+Iranian_Jew @ 3.993739
7 Assyrian+Iraqi_Jew @ 4.016468
8 Iraqi_Jew+Iraqi_Mandaean @ 4.050636
9 Iraqi_Jewish+Iraqi_Mandaean @ 4.092513
10 Iranian_Jewish+Iraqi_Jew @ 4.116803
11 Assyrian+Iraqi_Jewish @ 4.122672
12 Assyrian+Iranian_Jew @ 4.17181
13 Armenian+Iraqi_Jew @ 4.203209
14 Iranian_Jew+Iraqi_Mandaean @ 4.226016
15 Assyrian+Assyrian @ 4.232335
16 Iranian_Jewish+Iraqi_Jewish @ 4.232409
17 Armenian+Iraqi_Jewish @ 4.303148
18 Iranian_Jew+Iranian_Jewish @ 4.382085
19 Armenian+Assyrian @ 4.40713
20 Armenian+Iranian_Jew @ 4.437168
21528 iterations.

Using 3 populations approximation:
1 50% Iraqi_Jew +25% Iraqi_Jew +25% Iraqi_Jewish @ 3.619472
2 50% Iraqi_Jew +25% Iranian_Jew +25% Iraqi_Jew @ 3.642487
3 50% Iraqi_Jew +25% Iraqi_Jewish +25% Iraqi_Jewish @ 3.695507
4 50% Iraqi_Jew +25% Iranian_Jew +25% Iraqi_Jewish @ 3.700981
5 50% Iranian_Jew +25% Iraqi_Jew +25% Iraqi_Jew @ 3.743942
6 50% Iraqi_Jewish +25% Iranian_Jew +25% Iraqi_Jew @ 3.77053
7 50% Iraqi_Jewish +25% Iraqi_Jew +25% Iraqi_Jewish @ 3.776774
8 50% Iranian_Jew +25% Iraqi_Jew +25% Iraqi_Jewish @ 3.793977
9 50% Iraqi_Jew +25% Iraqi_Jew +25% Iraqi_Mandaean @ 3.812739
10 50% Iraqi_Jew +25% Iranian_Jewish +25% Iraqi_Jew @ 3.840807
11 50% Iraqi_Jew +25% Assyrian +25% Iraqi_Jew @ 3.845784
12 50% Iraqi_Jewish +25% Iranian_Jew +25% Iraqi_Jewish @ 3.845959
13 50% Iraqi_Jew +25% Iraqi_Jewish +25% Iraqi_Mandaean @ 3.849038
14 50% Iranian_Jew +25% Iraqi_Jewish +25% Iraqi_Jewish @ 3.855893
15 50% Iranian_Jew +25% Iranian_Jew +25% Iraqi_Jew @ 3.860035
16 50% Iraqi_Jew +25% Iranian_Jew +25% Iraqi_Mandaean @ 3.898565
17 50% Iraqi_Jew +25% Assyrian +25% Iraqi_Jewish @ 3.898973
18 50% Iranian_Jew +25% Iranian_Jew +25% Iraqi_Jewish @ 3.89925
19 50% Iraqi_Jew +25% Iranian_Jewish +25% Iraqi_Jewish @ 3.899553
20 50% Iraqi_Jewish +25% Iraqi_Jew +25% Iraqi_Mandaean @ 3.903277
2633115 iterations.

Using 4 populations approximation:
1 Iraqi_Jew+Iraqi_Jew+Iraqi_Jew+Iraqi_Jew @ 3.554062
2 Iraqi_Jew+Iraqi_Jew+Iraqi_Jew+Iraqi_Jewish @ 3.619472
3 Iranian_Jew+Iraqi_Jew+Iraqi_Jew+Iraqi_Jew @ 3.642487
4 Iraqi_Jew+Iraqi_Jew+Iraqi_Jewish+Iraqi_Jewish @ 3.695507
5 Iranian_Jew+Iraqi_Jew+Iraqi_Jew+Iraqi_Jewish @ 3.700981
6 Iranian_Jew+Iranian_Jew+Iraqi_Jew+Iraqi_Jew @ 3.743942
7 Iranian_Jew+Iraqi_Jew+Iraqi_Jewish+Iraqi_Jewish @ 3.77053
8 Iraqi_Jew+Iraqi_Jewish+Iraqi_Jewish+Iraqi_Jewish @ 3.776774
9 Iranian_Jew+Iranian_Jew+Iraqi_Jew+Iraqi_Jewish @ 3.793977
10 Iraqi_Jew+Iraqi_Jew+Iraqi_Jew+Iraqi_Mandaean @ 3.812739
11 Iranian_Jewish+Iraqi_Jew+Iraqi_Jew+Iraqi_Jew @ 3.840807
12 Assyrian+Iraqi_Jew+Iraqi_Jew+Iraqi_Jew @ 3.845784
13 Iranian_Jew+Iraqi_Jewish+Iraqi_Jewish+Iraqi_Jewish @ 3.845959
14 Iraqi_Jew+Iraqi_Jew+Iraqi_Jewish+Iraqi_Mandaean @ 3.849038
15 Iranian_Jew+Iranian_Jew+Iraqi_Jewish+Iraqi_Jewish @ 3.855893
16 Iranian_Jew+Iranian_Jew+Iranian_Jew+Iraqi_Jew @ 3.860035
17 Iraqi_Jewish+Iraqi_Jewish+Iraqi_Jewish+Iraqi_Jewis h @ 3.860179
18 Iranian_Jew+Iraqi_Jew+Iraqi_Jew+Iraqi_Mandaean @ 3.898565
19 Assyrian+Iraqi_Jew+Iraqi_Jew+Iraqi_Jewish @ 3.898973
20 Iranian_Jew+Iranian_Jew+Iranian_Jew+Iraqi_Jewish @ 3.89925
21 Iranian_Jewish+Iraqi_Jew+Iraqi_Jew+Iraqi_Jewish @ 3.899553
22 Iraqi_Jew+Iraqi_Jewish+Iraqi_Jewish+Iraqi_Mandaean @ 3.903277
23 Assyrian+Iranian_Jew+Iraqi_Jew+Iraqi_Jew @ 3.925104
24 Iranian_Jew+Iraqi_Jew+Iraqi_Jewish+Iraqi_Mandaean @ 3.930952
25 Iranian_Jew+Iranian_Jewish+Iraqi_Jew+Iraqi_Jew @ 3.949221
26 Assyrian+Iraqi_Jew+Iraqi_Jewish+Iraqi_Jewish @ 3.961977
27 Iranian_Jewish+Iraqi_Jew+Iraqi_Jewish+Iraqi_Jewish @ 3.96694
28 Iraqi_Jewish+Iraqi_Jewish+Iraqi_Jewish+Iraqi_Manda ean @ 3.967555
29 Assyrian+Iranian_Jew+Iraqi_Jew+Iraqi_Jewish @ 3.97359
30 Iranian_Jew+Iraqi_Jewish+Iraqi_Jewish+Iraqi_Mandae an @ 3.980725
31 Armenian+Iraqi_Jew+Iraqi_Jew+Iraqi_Jew @ 3.985949
32 Iranian_Jew+Iranian_Jew+Iranian_Jew+Iranian_Jew @ 3.993739
33 Iranian_Jew+Iranian_Jew+Iraqi_Jew+Iraqi_Mandaean @ 3.99533
34 Georgian+Iraqi_Jew+Iraqi_Jew+Iraqi_Jew @ 3.997072
35 Iranian_Jew+Iranian_Jewish+Iraqi_Jew+Iraqi_Jewish @ 4.000368
36 Assyrian+Iranian_Jew+Iranian_Jew+Iraqi_Jew @ 4.014439
37 Assyrian+Assyrian+Iraqi_Jew+Iraqi_Jew @ 4.016468
38 Iranian_Jew+Iranian_Jew+Iraqi_Jewish+Iraqi_Mandaea n @ 4.022314
39 Assyrian+Iraqi_Jewish+Iraqi_Jewish+Iraqi_Jewish @ 4.03024
40 Assyrian+Iranian_Jew+Iraqi_Jewish+Iraqi_Jewish @ 4.031937
18237060 iterations.

[Dr_McNinja]

Afghan Pashtuns and Utah Germans are now in the spreadsheet. But it might be useful to remove the extreme outliers from each group for any oracle type stuff.

Can you link to it? The link a few pages back is the same one without the two. Or copy/paste just the averages for the two new populations.

[Generalissimo]

Can you link to it? The link a few pages back is the same one without the two. Or copy/paste just the averages for the two new populations.

I can see them here...

https://docs.google.com/spreadsheets/d/1M2drQQD7jvwwaTkpFTuBLQXllkUTVNOIfa9FReH7V5M/edit?usp=sharing

[evon]

Me:

Oceanian 1.00E-05
European 0.563769
EEF 0.27463
East_Asian 0.001006
South_Asian 1.00E-05
Central_Asian 0.152004
Amerindian 0.008551
Siberian 1.00E-05
Sub-Saharan 1.00E-05

I dont have Oracle/R installed on this computer, so would someone please run me though the gauntlet?

https://s-media-cache-ak0.pinimg.com/originals/78/7f/ca/787fcac5037808e6e9d81e5503a0964a.jpg

[shazou]

K9

Oceanian 0.018288
Siberian 0.032883
Sub-Saharan 1E-005
East_Asian 0.867291
Central_Asian 0.00797
South_Asian 0.037068
Amerindian 0.011493
EEF 0.011353
European 0.013644

[evon]

Me:

Oceanian 1.00E-05
European 0.563769
EEF 0.27463
East_Asian 0.001006
South_Asian 1.00E-05
Central_Asian 0.152004
Amerindian 0.008551
Siberian 1.00E-05
Sub-Saharan 1.00E-05



Oracle thanks to Noel:

Least-squares method.

Using 1 population approximation:
1 Icelandic @ 2.627578
2 Bell_Beaker_LN @ 2.704801
3 Norwegian @ 2.930283
4 Utah_Scandinavian @ 3.124667
5 Orcadian @ 3.885409
6 Scottish @ 4.439593
7 Utah_German @ 5.886465
8 Czech @ 6.612001
9 English @ 6.915792
10 Ukrainian_Kharkov @ 7.488757
11 Polish @ 7.514131
12 Ukrainian_Poltava @ 7.597512
13 Ukrainian_Lviv @ 8.197735
14 Belarusian @ 8.760252
15 Ukrainian @ 9.478716
16 Hungarian @ 10.835493
17 Russian @ 11.643134
18 HungaryGamba_BA @ 12.419232
19 Estonian @ 13.302832
20 Lithuanian @ 13.450916
208 iterations.

Using 2 populations approximation:
1 HungaryGamba_BA+Lithuanian @ 1.429472
2 Estonian+HungaryGamba_BA @ 1.557434
3 Bell_Beaker_LN+Icelandic @ 2.507537
4 Bell_Beaker_LN+Norwegian @ 2.541642
5 Icelandic+Icelandic @ 2.627578
6 Bell_Beaker_LN+Scottish @ 2.678939
7 French+Lithuanian @ 2.700562
8 Bell_Beaker_LN+Bell_Beaker_LN @ 2.704801
9 Icelandic+Norwegian @ 2.736933
10 Bell_Beaker_LN+Orcadian @ 2.786434
11 Bell_Beaker_LN+Utah_Scandinavian @ 2.797307
12 Icelandic+Utah_Scandinavian @ 2.851878
13 Norwegian+Norwegian @ 2.930283
14 Loschbour+Turkish_Jew @ 2.930361
15 Norwegian+Utah_Scandinavian @ 2.955596
16 Loschbour+Sephardic_Jewish @ 3.121404
17 Utah_Scandinavian+Utah_Scandinavian @ 3.124667
18 Icelandic+Orcadian @ 3.161582
19 Bell_Beaker_LN+Utah_German @ 3.163471
20 Estonian+French @ 3.190824
21736 iterations.

Using 3 populations approximation:
1 50% Polish +25% Czech +25% Neolithic_Hungary @ 0.723587
2 50% Lithuanian +25% Orcadian +25% Spanish_North @ 0.85967
3 50% Polish +25% Neolithic_Hungary +25% Orcadian @ 0.860135
4 50% Lithuanian +25% Montenegrin +25% Neolithic_Hungary @ 0.874025
5 50% Polish +25% Neolithic_Hungary +25% Scottish @ 0.969711
6 50% Lithuanian +25% Czech +25% Spanish_North @ 0.976046
7 50% Lithuanian +25% Macedonian +25% Neolithic_Hungary @ 0.987784
8 50% Czech +25% Lithuanian +25% Neolithic_Hungary @ 1.005241
9 50% Lithuanian +25% French_South +25% Orcadian @ 1.019299
10 50% Polish +25% Neolithic_Hungary +25% Utah_German @ 1.037126
11 50% Neolithic_Hungary +25% Georgian +25% Loschbour @ 1.039867
12 50% Lithuanian +25% Scottish +25% Spanish_North @ 1.070281
13 50% Polish +25% Basque +25% Lithuanian @ 1.077807
14 50% Orcadian +25% Loschbour +25% South_Italian @ 1.097716
15 50% Lithuanian +25% Basque +25% Ukrainian_Poltava @ 1.116678
16 50% Lithuanian +25% Icelandic +25% Spanish_North @ 1.121988
17 50% Lithuanian +25% French +25% HungaryGamba_BA @ 1.128652
18 50% Belarusian +25% Neolithic_Hungary +25% Utah_German @ 1.128674
19 50% Lithuanian +25% Neolithic_Hungary +25% Serbian @ 1.1533
20 50% Lithuanian +25% French_South +25% Icelandic @ 1.155533
1770383 iterations.

Using 4 populations approximation:
1 Czech+Neolithic_Hungary+Polish+Polish @ 0.723587
2 Croatian+Lithuanian+Neolithic_Hungary+Polish @ 0.832826
3 Lithuanian+Lithuanian+Orcadian+Spanish_North @ 0.85967
4 Neolithic_Hungary+Orcadian+Polish+Polish @ 0.860135
5 Lithuanian+Lithuanian+Montenegrin+Neolithic_Hungar y @ 0.874025
6 Lithuanian+Neolithic_Hungary+Polish+Serbian_Bosnia @ 0.877082
7 Icelandic+Neolithic_Hungary+Polish+Ukrainian_Polta va @ 0.885338
8 Neolithic_Hungary+Orcadian+Polish+Ukrainian_Kharko v @ 0.904767
9 Bell_Beaker_LN+Neolithic_Hungary+Polish+Ukrainian_ Poltava @ 0.925872
10 Icelandic+Neolithic_Hungary+Polish+Ukrainian_Lviv @ 0.92711
11 Icelandic+Neolithic_Hungary+Polish+Ukrainian @ 0.929851
12 Belarusian+Czech+Neolithic_Hungary+Polish @ 0.931281
13 Neolithic_Hungary+Polish+Ukrainian_Poltava+Utah_Sc andinavian @ 0.952346
14 Neolithic_Hungary+Polish+Polish+Scottish @ 0.969711
15 Belarusian+Icelandic+Neolithic_Hungary+Ukrainian_P oltava @ 0.975906
16 Czech+Lithuanian+Lithuanian+Spanish_North @ 0.976046
17 Bergamo+Loschbour+Macedonian+Polish @ 0.977768
18 Neolithic_Hungary+Orcadian+Polish+Ukrainian @ 0.981244
19 Lithuanian+Lithuanian+Macedonian+Neolithic_Hungary @ 0.987784
20 Belarusian+Neolithic_Hungary+Orcadian+Polish @ 0.99615
21 Czech+Czech+Lithuanian+Neolithic_Hungary @ 1.005241
22 Belarusian+Neolithic_Hungary+Polish+Scottish @ 1.009143
23 Belarusian+Croatian+Lithuanian+Neolithic_Hungary @ 1.014103
24 Neolithic_Hungary+Orcadian+Polish+Ukrainian_Lviv @ 1.015616
25 Hungarian+Lithuanian+Neolithic_Hungary+Ukrainian_P oltava @ 1.017917
26 French_South+Lithuanian+Lithuanian+Orcadian @ 1.019299
27 Bell_Beaker_LN+HungaryGamba_BA+Lithuanian+Scottish @ 1.019363
28 Belarusian+Neolithic_Hungary+Polish+Utah_German @ 1.020658
29 Bell_Beaker_LN+Neolithic_Hungary+Polish+Ukrainian_ Lviv @ 1.021762
30 Neolithic_Hungary+Polish+Polish+Utah_German @ 1.037126
31 Georgian+Loschbour+Neolithic_Hungary+Neolithic_Hun gary @ 1.039867
32 Neolithic_Hungary+Orcadian+Polish+Ukrainian_Poltav a @ 1.039879
33 Neolithic_Hungary+Polish+Ukrainian_Lviv+Utah_Scand inavian @ 1.040131
34 Belarusian+Neolithic_Hungary+Orcadian+Ukrainian_Kh arkov @ 1.042146
35 Icelandic+Neolithic_Hungary+Polish+Ukrainian_Khark ov @ 1.052231
36 English+Loschbour+Macedonian+Montenegrin @ 1.053236
37 Loschbour+Orcadian+Serbian_Bosnia+Tuscan @ 1.056929
38 Bell_Beaker_LN+Neolithic_Hungary+Polish+Ukrainian @ 1.062403
39 Icelandic+Loschbour+Orcadian+South_Italian @ 1.064151
40 Belarusian+Bell_Beaker_LN+Neolithic_Hungary+Ukrain ian_Poltava @ 1.065567
4657407 iterations.


Gaussian method.
Noise dispersion set to 0.584552

Using 1 population approximation:
1 Orcadian @ 2.892325
2 Icelandic @ 3.124892
3 Bell_Beaker_LN @ 3.391706
4 Scottish @ 3.578351
5 English @ 3.712807
6 Norwegian @ 3.817934
7 Czech @ 3.983408
8 Utah_German @ 4.010773
9 Utah_Scandinavian @ 4.094051
10 HungaryGamba_BA @ 4.173653
11 Polish @ 4.177198
12 Ukrainian_Poltava @ 4.484638
13 Ukrainian_Kharkov @ 4.553231
14 Ukrainian_Lviv @ 4.899479
15 Hungarian @ 4.985993
16 Belarusian @ 5.062002
17 Ukrainian @ 5.23585
18 Croatian @ 5.415427
19 French @ 5.438601
20 Lithuanian @ 5.518937
208 iterations.

Using 2 populations approximation:
1 HungaryGamba_BA+Lithuanian @ 2.713862
2 HungaryGamba_BA+Polish @ 2.834135
3 HungaryGamba_BA+Orcadian @ 2.840855
4 Orcadian+Orcadian @ 2.892325
5 HungaryGamba_BA+Icelandic @ 2.939648
6 Bell_Beaker_LN+HungaryGamba_BA @ 2.98043
7 Icelandic+Orcadian @ 3.015397
8 Icelandic+Icelandic @ 3.124892
9 Bell_Beaker_LN+Orcadian @ 3.135175
10 Bell_Beaker_LN+Icelandic @ 3.279861
11 English+Orcadian @ 3.281803
12 Orcadian+Scottish @ 3.28274
13 English+Icelandic @ 3.326211
14 Icelandic+Scottish @ 3.329099
15 Bell_Beaker_LN+English @ 3.357502
16 HungaryGamba_BA+Scottish @ 3.371475
17 Bell_Beaker_LN+Bell_Beaker_LN @ 3.391706
18 HungaryGamba_BA+Ukrainian_Kharkov @ 3.411323
19 HungaryGamba_BA+Ukrainian_Poltava @ 3.413506
20 Czech+HungaryGamba_BA @ 3.429657
21736 iterations.

Using 3 populations approximation:
1 50% HungaryGamba_BA +25% Lithuanian +25% Orcadian @ 2.579077
2 50% HungaryGamba_BA +25% Icelandic +25% Lithuanian @ 2.672628
3 50% Orcadian +25% HungaryGamba_BA +25% Orcadian @ 2.685003
4 50% HungaryGamba_BA +25% Lithuanian +25% Polish @ 2.686938
5 50% Orcadian +25% HungaryGamba_BA +25% Lithuanian @ 2.698103
6 50% HungaryGamba_BA +25% Lithuanian +25% Lithuanian @ 2.713862
7 50% Orcadian +25% Neolithic_Hungary +25% Orcadian @ 2.714308
8 50% HungaryGamba_BA +25% Bell_Beaker_LN +25% Lithuanian @ 2.71915
9 50% Orcadian +25% HungaryGamba_BA +25% Icelandic @ 2.741899
10 50% Orcadian +25% Bell_Beaker_LN +25% HungaryGamba_BA @ 2.782691
11 50% Icelandic +25% HungaryGamba_BA +25% Orcadian @ 2.793328
12 50% Orcadian +25% Icelandic +25% Neolithic_Hungary @ 2.809393
13 50% Orcadian +25% Lithuanian +25% Neolithic_Hungary @ 2.812961
14 50% HungaryGamba_BA +25% Orcadian +25% Polish @ 2.816561
15 50% Orcadian +25% Neolithic_Hungary +25% Polish @ 2.822713
16 50% HungaryGamba_BA +25% Lithuanian +25% Scottish @ 2.823808
17 50% HungaryGamba_BA +25% Polish +25% Polish @ 2.834135
18 50% Orcadian +25% HungaryGamba_BA +25% Polish @ 2.840738
19 50% HungaryGamba_BA +25% Orcadian +25% Orcadian @ 2.840855
20 50% Icelandic +25% HungaryGamba_BA +25% Icelandic @ 2.842648
2713922 iterations.

Using 4 populations approximation:
1 HungaryGamba_BA+HungaryGamba_BA+Lithuanian+Orcadia n @ 2.579077
2 HungaryGamba_BA+HungaryGamba_BA+Icelandic+Lithuani an @ 2.672628
3 HungaryGamba_BA+Orcadian+Orcadian+Orcadian @ 2.685003
4 HungaryGamba_BA+HungaryGamba_BA+Lithuanian+Polish @ 2.686938
5 HungaryGamba_BA+Lithuanian+Orcadian+Orcadian @ 2.698103
6 HungaryGamba_BA+HungaryGamba_BA+Lithuanian+Lithuan ian @ 2.713862
7 Neolithic_Hungary+Orcadian+Orcadian+Orcadian @ 2.714308
8 Bell_Beaker_LN+HungaryGamba_BA+HungaryGamba_BA+Lit huanian @ 2.71915
9 HungaryGamba_BA+Icelandic+Orcadian+Orcadian @ 2.741899
10 HungaryGamba_BA+Icelandic+Lithuanian+Orcadian @ 2.781576
11 Bell_Beaker_LN+HungaryGamba_BA+Orcadian+Orcadian @ 2.782691
12 HungaryGamba_BA+Icelandic+Icelandic+Orcadian @ 2.793328
13 Icelandic+Neolithic_Hungary+Orcadian+Orcadian @ 2.809393
14 Lithuanian+Neolithic_Hungary+Orcadian+Orcadian @ 2.812961
15 HungaryGamba_BA+HungaryGamba_BA+Orcadian+Polish @ 2.816561
16 Neolithic_Hungary+Orcadian+Orcadian+Polish @ 2.822713
17 HungaryGamba_BA+HungaryGamba_BA+Lithuanian+Scottis h @ 2.823808
18 HungaryGamba_BA+HungaryGamba_BA+Polish+Polish @ 2.834135
19 HungaryGamba_BA+Orcadian+Orcadian+Polish @ 2.840738
20 HungaryGamba_BA+HungaryGamba_BA+Orcadian+Orcadian @ 2.840855
21 HungaryGamba_BA+Icelandic+Icelandic+Icelandic @ 2.842648
22 Bell_Beaker_LN+HungaryGamba_BA+Icelandic+Orcadian @ 2.845529
23 HungaryGamba_BA+HungaryGamba_BA+Icelandic+Polish @ 2.861268
24 Czech+HungaryGamba_BA+HungaryGamba_BA+Lithuanian @ 2.861286
25 HungaryGamba_BA+Icelandic+Icelandic+Lithuanian @ 2.864293
26 Bell_Beaker_LN+HungaryGamba_BA+Lithuanian+Orcadian @ 2.867332
27 English+HungaryGamba_BA+Lithuanian+Orcadian @ 2.871243
28 Georgian+Loschbour+Neolithic_Hungary+Neolithic_Hun gary @ 2.874813
29 Bell_Beaker_LN+Neolithic_Hungary+Orcadian+Orcadian @ 2.875463
30 Bell_Beaker_LN+Bell_Beaker_LN+HungaryGamba_BA+Orca dian @ 2.882805
31 HungaryGamba_BA+Icelandic+Orcadian+Polish @ 2.887038
32 HungaryGamba_BA+Lithuanian+Orcadian+Scottish @ 2.888641
33 HungaryGamba_BA+HungaryGamba_BA+Icelandic+Orcadian @ 2.891336
34 Orcadian+Orcadian+Orcadian+Orcadian @ 2.892325
35 Icelandic+Icelandic+Neolithic_Hungary+Orcadian @ 2.89691
36 Bell_Beaker_LN+HungaryGamba_BA+HungaryGamba_BA+Pol ish @ 2.897964
37 Bell_Beaker_LN+HungaryGamba_BA+Icelandic+Icelandic @ 2.902915
38 Icelandic+Neolithic_Hungary+Orcadian+Polish @ 2.90497
39 Bell_Beaker_LN+HungaryGamba_BA+HungaryGamba_BA+Orc adian @ 2.907019
40 HungaryGamba_BA+Lithuanian+Neolithic_Hungary+Orcad ian @ 2.917905
17531592 iterations.

[Jessie]

Noel kindly did my Oracle as well.

Least-squares method.

Using 1 population approximation:
1 Scottish @ 1.503039
2 Utah_German @ 1.537972
3 English @ 2.597357
4 Orcadian @ 2.793485
5 Czech @ 3.397836
6 Norwegian @ 3.745461
7 Icelandic @ 4.27367
8 Utah_Scandinavian @ 4.762585
9 Bell_Beaker_LN @ 5.871907
10 Hungarian @ 6.31439
11 Ukrainian_Poltava @ 6.949187
12 Ukrainian_Lviv @ 7.745619
13 Ukrainian_Kharkov @ 8.274837
14 Ukrainian @ 9.196926
15 Polish @ 9.507252
16 Croatian @ 9.88315
17 Serbian_Bosnia @ 10.304231
18 HungaryGamba_BA @ 10.487227
19 Belarusian @ 10.600791
20 Bosnian @ 10.934961
208 iterations.

Using 2 populations approximation:
1 English+Orcadian @ 1.133304
2 English+Norwegian @ 1.239949
3 Scottish+Utah_German @ 1.262112
4 English+Scottish @ 1.366742
5 English+Icelandic @ 1.382281
6 Scottish+Scottish @ 1.503039
7 Utah_German+Utah_German @ 1.537972
8 Orcadian+Utah_German @ 1.573353
9 English+Utah_Scandinavian @ 1.599306
10 HungaryGamba_BA+Ukrainian @ 1.633067
11 Norwegian+Utah_German @ 1.824982
12 French+Polish @ 1.901252
13 English+Utah_German @ 1.907997
14 Cypriot+Loschbour @ 1.990657
15 HungaryGamba_BA+Ukrainian_Lviv @ 1.990757
16 Icelandic+Utah_German @ 2.023983
17 Bell_Beaker_LN+English @ 2.037088
18 Orcadian+Scottish @ 2.056768
19 Czech+English @ 2.080286
20 Belarusian+French @ 2.123476
21736 iterations.

Using 3 populations approximation:
1 50% Icelandic +25% French +25% Orcadian @ 1.018289
2 50% Orcadian +25% Bell_Beaker_LN +25% French @ 1.064036
3 50% English +25% Bell_Beaker_LN +25% Utah_German @ 1.072928
4 50% English +25% Icelandic +25% Scottish @ 1.082223
5 50% Icelandic +25% French +25% Norwegian @ 1.093389
6 50% English +25% Norwegian +25% Orcadian @ 1.102865
7 50% English +25% Norwegian +25% Scottish @ 1.103116
8 50% Utah_German +25% English +25% Icelandic @ 1.104464
9 50% English +25% Icelandic +25% Utah_German @ 1.10499
10 50% Icelandic +25% French +25% Icelandic @ 1.107298
11 50% Utah_Scandinavian +25% French +25% Orcadian @ 1.118041
12 50% Utah_German +25% English +25% Norwegian @ 1.128287
13 50% French +25% Icelandic +25% Lithuanian @ 1.131257
14 50% English +25% Orcadian +25% Orcadian @ 1.133304
15 50% English +25% Utah_German +25% Utah_Scandinavian @ 1.135416
16 50% English +25% Scottish +25% Utah_Scandinavian @ 1.135652
17 50% Norwegian +25% French +25% Icelandic @ 1.136736
18 50% Orcadian +25% French +25% Utah_Scandinavian @ 1.153819
19 50% English +25% Bell_Beaker_LN +25% English @ 1.154225
20 50% French +25% Lithuanian +25% Utah_Scandinavian @ 1.157975
1771517 iterations.

Using 4 populations approximation:
1 Basque+Corded_Ware_LN+HungaryGamba_BA+Polish @ 0.921336
2 French+Icelandic+Icelandic+Orcadian @ 1.018289
3 Basque+Belarusian+Corded_Ware_LN+HungaryGamba_BA @ 1.02278
4 Basque+Iranian_Jew+Lithuanian+Loschbour @ 1.039427
5 French+Icelandic+Orcadian+Utah_Scandinavian @ 1.045612
6 Iraqi_Jew+Lithuanian+Loschbour+Spanish_North @ 1.047796
7 French+Icelandic+Norwegian+Orcadian @ 1.061367
8 Bell_Beaker_LN+French+Orcadian+Orcadian @ 1.064036
9 Bell_Beaker_LN+English+English+Utah_German @ 1.072928
10 English+English+Icelandic+Scottish @ 1.082223
11 French+Norwegian+Orcadian+Utah_Scandinavian @ 1.08941
12 French+Icelandic+Icelandic+Norwegian @ 1.093389
13 Bell_Beaker_LN+French+Norwegian+Orcadian @ 1.099429
14 English+English+Norwegian+Orcadian @ 1.102865
15 English+English+Norwegian+Scottish @ 1.103116
16 English+Icelandic+Utah_German+Utah_German @ 1.104464
17 English+English+Icelandic+Utah_German @ 1.10499
18 Bell_Beaker_LN+French+Icelandic+Orcadian @ 1.105788
19 French+Icelandic+Icelandic+Icelandic @ 1.107298
20 French+Orcadian+Utah_Scandinavian+Utah_Scandinavia n @ 1.118041
21 Bosnian+French_South+Lithuanian+Polish @ 1.124821
22 English+Norwegian+Utah_German+Utah_German @ 1.128287
23 French+French+Icelandic+Lithuanian @ 1.131257
24 Bosnian+English+HungaryGamba_BA+Lithuanian @ 1.132151
25 English+English+Orcadian+Orcadian @ 1.133304
26 English+English+Utah_German+Utah_Scandinavian @ 1.135416
27 English+English+Scottish+Utah_Scandinavian @ 1.135652
28 Iraqi_Jewish+Lithuanian+Loschbour+Spanish_North @ 1.136102
29 French+Icelandic+Norwegian+Norwegian @ 1.136736
30 Bosnian+Corded_Ware_LN+HungaryGamba_BA+Neolithic_H ungary @ 1.137641
31 Bell_Beaker_LN+French+Icelandic+Scottish @ 1.138022
32 Bell_Beaker_LN+Czech+French+Icelandic @ 1.152644
33 French+Icelandic+Norwegian+Utah_Scandinavian @ 1.153675
34 French+Orcadian+Orcadian+Utah_Scandinavian @ 1.153819
35 Bell_Beaker_LN+English+English+English @ 1.154225
36 French+French+Lithuanian+Utah_Scandinavian @ 1.157975
37 French+Icelandic+Scottish+Utah_Scandinavian @ 1.158667
38 French+Norwegian+Norwegian+Orcadian @ 1.159036
39 French_South+Iraqi_Jew+Lithuanian+Loschbour @ 1.159508
40 English+English+Icelandic+Orcadian @ 1.160331
5338338 iterations.


Gaussian method.
Noise dispersion set to 0.584552

Using 1 population approximation:
1 Orcadian @ 2.788039
2 English @ 3.224925
3 Icelandic @ 3.274491
4 Scottish @ 3.444177
5 Utah_German @ 3.676277
6 Bell_Beaker_LN @ 3.68285
7 Norwegian @ 3.793994
8 Czech @ 3.943959
9 Utah_Scandinavian @ 4.24133
10 Hungarian @ 4.625269
11 French @ 4.647304
12 HungaryGamba_BA @ 4.694288
13 Ukrainian_Kharkov @ 4.762205
14 Polish @ 4.809033
15 Bosnian @ 4.931483
16 Ukrainian_Poltava @ 4.970049
17 Ukrainian_Lviv @ 4.974974
18 Serbian_Bosnia @ 5.025832
19 Croatian @ 5.286401
20 Ukrainian @ 5.477253
208 iterations.

Using 2 populations approximation:
1 Orcadian+Orcadian @ 2.788039
2 HungaryGamba_BA+Orcadian @ 2.864422
3 English+Orcadian @ 2.980124
4 Icelandic+Orcadian @ 3.050557
5 HungaryGamba_BA+Icelandic @ 3.060864
6 English+Icelandic @ 3.131134
7 Bell_Beaker_LN+HungaryGamba_BA @ 3.145071
8 Orcadian+Scottish @ 3.16419
9 English+English @ 3.224925
10 Bell_Beaker_LN+Orcadian @ 3.246708
11 Bell_Beaker_LN+English @ 3.2561
12 Icelandic+Icelandic @ 3.274491
13 Orcadian+Utah_German @ 3.288908
14 Icelandic+Scottish @ 3.327959
15 English+Scottish @ 3.343608
16 HungaryGamba_BA+Norwegian @ 3.388526
17 HungaryGamba_BA+Scottish @ 3.397742
18 French+Orcadian @ 3.403516
19 Norwegian+Orcadian @ 3.405736
20 HungaryGamba_BA+Polish @ 3.422515
21736 iterations.

Using 3 populations approximation:
1 50% Orcadian +25% HungaryGamba_BA +25% Orcadian @ 2.573281
2 50% Orcadian +25% HungaryGamba_BA +25% Icelandic @ 2.705324
3 50% HungaryGamba_BA +25% Corded_Ware_LN +25% HungaryGamba_BA @ 2.740029
4 50% Orcadian +25% Bell_Beaker_LN +25% HungaryGamba_BA @ 2.779174
5 50% Orcadian +25% English +25% HungaryGamba_BA @ 2.802137
6 50% Icelandic +25% HungaryGamba_BA +25% Orcadian @ 2.822447
7 50% Orcadian +25% HungaryGamba_BA +25% Scottish @ 2.850788
8 50% HungaryGamba_BA +25% Orcadian +25% Orcadian @ 2.864422
9 50% Orcadian +25% English +25% Orcadian @ 2.878101
10 50% Orcadian +25% Icelandic +25% Orcadian @ 2.926153
11 50% Icelandic +25% HungaryGamba_BA +25% Icelandic @ 2.929565
12 50% Orcadian +25% HungaryGamba_BA +25% Utah_German @ 2.937599
13 50% Orcadian +25% HungaryGamba_BA +25% Norwegian @ 2.945392
14 50% Orcadian +25% French +25% Orcadian @ 2.965877
15 50% HungaryGamba_BA +25% Icelandic +25% Orcadian @ 2.968097
16 50% Orcadian +25% Czech +25% HungaryGamba_BA @ 2.969012
17 50% HungaryGamba_BA +25% Armenian +25% Loschbour @ 2.971071
18 50% HungaryGamba_BA +25% Corded_Ware_LN +25% Orcadian @ 2.971324
19 50% Orcadian +25% Orcadian +25% Spanish_North @ 2.972017
20 50% Icelandic +25% English +25% HungaryGamba_BA @ 2.97823
2872225 iterations.

Using 4 populations approximation:
1 HungaryGamba_BA+Orcadian+Orcadian+Orcadian @ 2.573281
2 HungaryGamba_BA+Icelandic+Orcadian+Orcadian @ 2.705324
3 Corded_Ware_LN+HungaryGamba_BA+HungaryGamba_BA+Hun garyGamba_BA @ 2.740029
4 Bell_Beaker_LN+HungaryGamba_BA+Orcadian+Orcadian @ 2.779174
5 Orcadian+Orcadian+Orcadian+Orcadian @ 2.788039
6 English+HungaryGamba_BA+Orcadian+Orcadian @ 2.802137
7 HungaryGamba_BA+Icelandic+Icelandic+Orcadian @ 2.822447
8 HungaryGamba_BA+Orcadian+Orcadian+Scottish @ 2.850788
9 HungaryGamba_BA+HungaryGamba_BA+Orcadian+Orcadian @ 2.864422
10 English+Orcadian+Orcadian+Orcadian @ 2.878101
11 English+HungaryGamba_BA+Icelandic+Orcadian @ 2.894717
12 Bell_Beaker_LN+HungaryGamba_BA+Icelandic+Orcadian @ 2.909482
13 Icelandic+Orcadian+Orcadian+Orcadian @ 2.926153
14 HungaryGamba_BA+Icelandic+Icelandic+Icelandic @ 2.929565
15 HungaryGamba_BA+Orcadian+Orcadian+Utah_German @ 2.937599
16 Bell_Beaker_LN+English+HungaryGamba_BA+Orcadian @ 2.941615
17 HungaryGamba_BA+Icelandic+Orcadian+Scottish @ 2.945205
18 HungaryGamba_BA+Norwegian+Orcadian+Orcadian @ 2.945392
19 French+Orcadian+Orcadian+Orcadian @ 2.965877
20 HungaryGamba_BA+HungaryGamba_BA+Icelandic+Orcadian @ 2.968097
21 Czech+HungaryGamba_BA+Orcadian+Orcadian @ 2.969012
22 Armenian+HungaryGamba_BA+HungaryGamba_BA+Loschbour @ 2.971071
23 Corded_Ware_LN+HungaryGamba_BA+HungaryGamba_BA+Orc adian @ 2.971324
24 Orcadian+Orcadian+Orcadian+Spanish_North @ 2.972017
25 Corded_Ware_LN+HungaryGamba_BA+Orcadian+Spanish_No rth @ 2.97817
26 English+HungaryGamba_BA+Icelandic+Icelandic @ 2.97823
27 Bell_Beaker_LN+Bell_Beaker_LN+HungaryGamba_BA+Orca dian @ 2.979987
28 English+English+Orcadian+Orcadian @ 2.980124
29 English+Icelandic+Orcadian+Orcadian @ 2.984698
30 Orcadian+Orcadian+Orcadian+Scottish @ 2.994099
31 HungaryGamba_BA+Orcadian+Orcadian+Polish @ 2.994933
32 Bell_Beaker_LN+HungaryGamba_BA+HungaryGamba_BA+Orc adian @ 2.998819
33 Bell_Beaker_LN+HungaryGamba_BA+Orcadian+Scottish @ 3.01723
34 English+English+HungaryGamba_BA+Orcadian @ 3.020865
35 Bell_Beaker_LN+Orcadian+Orcadian+Orcadian @ 3.023547
36 Bell_Beaker_LN+HungaryGamba_BA+Icelandic+Icelandic @ 3.02692
37 Corded_Ware_LN+English+HungaryGamba_BA+HungaryGamb a_BA @ 3.029452
38 Basque+Corded_Ware_LN+HungaryGamba_BA+Orcadian @ 3.029849
39 Bosnian+HungaryGamba_BA+Orcadian+Orcadian @ 3.030191
40 HungaryGamba_BA+Icelandic+Norwegian+Orcadian @ 3.031243
20625270 iterations.

[Kurd]

K9

Oceanian 0.018288
Siberian 0.032883
Sub-Saharan 1E-005
East_Asian 0.867291
Central_Asian 0.00797
South_Asian 0.037068
Amerindian 0.011493
EEF 0.011353
European 0.013644

Welcome to the forum :). Do you have Lahu or Kinh E Asian ancestry?

[SwampThing27]

Could someone do my updated oracle for me please? I only have the old single population spreadsheet.

Oceanian .03606%
European 48.95%
EEF 31.8246%
East_Asian .001%
South_Asian 02.1088%
Central_Asian 15.5131%
Amerindian .02273%
Siberian .001%
Sub-Saharan 1.0581%

[J Man]

Would someone be so kind to run my results through the updated Oracle as well please?

Oceanian-0.9%

European-46.0%

EEF-28.4%

East_Asian-1.3%

South_Asian-0.4%

Central_Asian-21.1%

Amerindian-0.7%

Siberia-0.8%

Sub-Saharan-0.0%

[ZephyrousMandaru]

Could someone do my updated oracle for me please? I only have the old single population spreadsheet.

Oceanian .03606%
European 48.95%
EEF 31.8246%
East_Asian .001%
South_Asian 02.1088%
Central_Asian 15.5131%
Amerindian .02273%
Siberian .001%
Sub-Saharan 1.0581%



Least-squares method.

Using 1 population approximation:
1 English @ 2.814375
2 Scottish @ 5.225865
3 Hungarian @ 5.310461
4 Czech @ 6.019018
5 Orcadian @ 6.796819
6 French @ 7.349667
7 Croatian @ 7.434427
8 Norwegian @ 7.723309
9 Serbian_Bosnia @ 8.188917
10 Icelandic @ 8.386232
11 HungaryGamba_BA @ 8.559361
12 Bosnian @ 8.931389
13 Bell_Beaker_LN @ 9.88983
14 Ukrainian_Poltava @ 10.151604
15 Ukrainian_Lviv @ 10.961969
16 Serbian @ 11.79602
17 Ukrainian_Kharkov @ 11.859008
18 Ukrainian @ 12.302771
19 Montenegrin @ 13.384107
20 Polish @ 13.411532
207 iterations.

Using 2 populations approximation:
1 Loschbour+Samaritan @ 1.933329
2 French+Norwegian @ 2.029898
3 French+Orcadian @ 2.117766
4 French+Icelandic @ 2.199483
5 French+Scottish @ 2.374296
6 Bell_Beaker_LN+French @ 2.52302
7 Czech+French @ 2.685647
8 English+English @ 2.814375
9 Lithuanian+Spanish @ 2.915391
10 Estonian+Spanish @ 2.978575
11 French+Ukrainian_Poltava @ 3.067991
12 Bergamo+Lithuanian @ 3.197327
13 French+Ukrainian_Lviv @ 3.268459
14 French+Ukrainian_Kharkov @ 3.274813
15 Hungarian+HungaryGamba_BA @ 3.283452
16 Motala12+Samaritan @ 3.327111
17 English+Hungarian @ 3.370048
18 Bergamo+Estonian @ 3.386585
19 Czech+HungaryGamba_BA @ 3.391636
20 English+French @ 3.488369
21528 iterations.

Using 3 populations approximation:
1 50% French_South +25% Corded_Ware_LN +25% Ukrainian_Kharkov @ 1.518788
2 50% French_South +25% Corded_Ware_LN +25% Ukrainian_Lviv @ 1.551562
3 50% French_South +25% Corded_Ware_LN +25% Ukrainian @ 1.560004
4 50% Sicilian +25% Bell_Beaker_LN +25% Loschbour @ 1.571663
5 50% French_South +25% Corded_Ware_LN +25% Polish @ 1.591722
6 50% French_South +25% Belarusian +25% Corded_Ware_LN @ 1.625195
7 50% French_South +25% Corded_Ware_LN +25% Ukrainian_Poltava @ 1.670261
8 50% Sicilian +25% Icelandic +25% Loschbour @ 1.686456
9 50% Sicilian +25% Loschbour +25% Norwegian @ 1.720345
10 50% West_Sicilian +25% Loschbour +25% Orcadian @ 1.760226
11 50% West_Sicilian +25% Loschbour +25% Scottish @ 1.770001
12 50% French +25% Lebanese_Muslim +25% Loschbour @ 1.797279
13 50% West_Sicilian +25% Loschbour +25% Norwegian @ 1.804845
14 50% French +25% Lebanese +25% Loschbour @ 1.809857
15 50% Scottish +25% Spanish +25% Ukrainian_Kharkov @ 1.83523
16 50% Lithuanian +25% Moroccan_Jew +25% Neolithic_Hungary @ 1.836683
17 50% Bell_Beaker_LN +25% Hungarian +25% Spanish @ 1.838886
18 50% Lithuanian +25% Libyan_Jew +25% Neolithic_Hungary @ 1.843367
19 50% Croatian +25% Libyan_Jew +25% Loschbour @ 1.845645
20 50% Norwegian +25% Czech +25% Spanish @ 1.856853
1992689 iterations.

Using 4 populations approximation:
1 Basque+English+Iranian_Jewish+Loschbour @ 1.316569
2 Basque+Iranian_Jew+Loschbour+Scottish @ 1.337322
3 Icelandic+Lebanese_Muslim+Loschbour+Spanish @ 1.367658
4 Basque+Iranian_Jew+Loschbour+Orcadian @ 1.413665
5 French_South+Iraqi_Jew+Loschbour+Norwegian @ 1.42389
6 Basque+Iraqi_Mandaean+Loschbour+Scottish @ 1.425438
7 Lebanese_Muslim+Loschbour+Norwegian+Spanish @ 1.432976
8 Bell_Beaker_LN+Lebanese_Muslim+Loschbour+Spanish @ 1.440944
9 French+HungaryGamba_BA+Loschbour+Syrian @ 1.460406
10 Lebanese_Muslim+Loschbour+Orcadian+Spanish @ 1.472187
11 French_South+Icelandic+Iraqi_Jew+Loschbour @ 1.475385
12 French_South+Iranian_Jew+Loschbour+Scottish @ 1.478344
13 Basque+Czech+Iranian_Jew+Loschbour @ 1.480613
14 French_South+Iraqi_Jew+Loschbour+Orcadian @ 1.492135
15 Basque+French+Kurdish+Loschbour @ 1.494891
16 Basque+Iraqi_Mandaean+Loschbour+Orcadian @ 1.496553
17 French_South+Iraqi_Jewish+Loschbour+Norwegian @ 1.500487
18 Iranian_Jew+Loschbour+Scottish+Spanish_North @ 1.503511
19 Corded_Ware_LN+French_South+French_South+Ukrainian _Kharkov @ 1.518788
20 Czech+French_South+Loschbour+Syrian @ 1.523823
21 Basque+Czech+Iraqi_Mandaean+Loschbour @ 1.525706
22 Basque+English+Iranian_Jew+Loschbour @ 1.529518
23 French_South+Iraqi_Mandaean+Loschbour+Scottish @ 1.531344
24 French_South+Iraqi_Jewish+Loschbour+Orcadian @ 1.531811
25 Icelandic+Loschbour+Spanish+Syrian @ 1.540015
26 Druze+French_South+Loschbour+Ukrainian @ 1.545188
27 Basque+Iranian_Jew+Loschbour+Norwegian @ 1.54761
28 French_South+Icelandic+Iraqi_Jewish+Loschbour @ 1.55027
29 Corded_Ware_LN+French_South+French_South+Ukrainian _Lviv @ 1.551562
30 Icelandic+Lebanese+Loschbour+Spanish @ 1.553363
31 French_South+Iraqi_Jew+Loschbour+Scottish @ 1.554568
32 Corded_Ware_LN+French_South+French_South+Ukrainian @ 1.560004
33 Iraqi_Mandaean+Loschbour+Scottish+Spanish_North @ 1.562244
34 French_South+Iraqi_Jewish+Loschbour+Scottish @ 1.570271
35 Bell_Beaker_LN+Loschbour+Sicilian+Sicilian @ 1.571663
36 Basque+English+Iraqi_Mandaean+Loschbour @ 1.575121
37 Druze+French_South+Loschbour+Ukrainian_Lviv @ 1.579327
38 Bell_Beaker_LN+French_South+Iraqi_Jew+Loschbour @ 1.591031
39 Bulgarian+Loschbour+Neolithic_Hungary+Syrian @ 1.591569
40 Corded_Ware_LN+French_South+French_South+Polish @ 1.591722
6767005 iterations.


Gaussian method.
Noise dispersion set to 0.584552

Using 1 population approximation:
1 Orcadian @ 4.208313
2 English @ 4.27034
3 French @ 4.425323
4 Scottish @ 4.570837
5 Icelandic @ 4.746287
6 Norwegian @ 4.959557
7 Bell_Beaker_LN @ 5.04877
8 Bosnian @ 5.221253
9 Czech @ 5.268793
10 Hungarian @ 5.583021
11 Serbian_Bosnia @ 5.948762
12 HungaryGamba_BA @ 6.135961
13 Ukrainian_Kharkov @ 6.25571
14 Croatian @ 6.48079
15 Ukrainian_Lviv @ 6.499833
16 Polish @ 6.635009
17 Serbian @ 6.637986
18 Ukrainian_Poltava @ 6.677546
19 Ukrainian @ 6.847449
20 Montenegrin @ 7.239959
207 iterations.

Using 2 populations approximation:
1 Basque+Corded_Ware_LN @ 3.72098
2 French+Orcadian @ 3.783625
3 Loschbour+Samaritan @ 3.816398
4 Corded_Ware_LN+Spanish_North @ 3.852617
5 French+Icelandic @ 3.926608
6 Lithuanian+Spanish @ 3.963427
7 Bell_Beaker_LN+French @ 3.972513
8 Orcadian+Spanish @ 4.01631
9 Polish+Spanish @ 4.043848
10 Icelandic+Spanish @ 4.04896
11 Bosnian+HungaryGamba_BA @ 4.089314
12 Bell_Beaker_LN+Spanish @ 4.090819
13 English+French @ 4.093627
14 Corded_Ware_LN+French_South @ 4.115594
15 French+Scottish @ 4.125112
16 HungaryGamba_BA+Orcadian @ 4.139919
17 French+Norwegian @ 4.158633
18 Corded_Ware_LN+Spain_MN @ 4.186074
19 English+Orcadian @ 4.197019
20 Orcadian+Orcadian @ 4.208313
21528 iterations.

Using 3 populations approximation:
1 50% Orcadian +25% Orcadian +25% Spanish @ 3.222418
2 50% HungaryGamba_BA +25% Iranian_Jew +25% Loschbour @ 3.222439
3 50% HungaryGamba_BA +25% Iraqi_Jew +25% Loschbour @ 3.227322
4 50% HungaryGamba_BA +25% Iranian_Jewish +25% Loschbour @ 3.253491
5 50% HungaryGamba_BA +25% Corded_Ware_LN +25% Spanish @ 3.253984
6 50% HungaryGamba_BA +25% Corded_Ware_LN +25% French_South @ 3.294261
7 50% Orcadian +25% Icelandic +25% Spanish @ 3.325169
8 50% HungaryGamba_BA +25% Iraqi_Mandaean +25% Loschbour @ 3.348462
9 50% Orcadian +25% Bell_Beaker_LN +25% Spanish @ 3.370585
10 50% HungaryGamba_BA +25% Basque +25% Corded_Ware_LN @ 3.388769
11 50% Spanish_North +25% Corded_Ware_LN +25% Orcadian @ 3.402899
12 50% Icelandic +25% Orcadian +25% Spanish @ 3.420409
13 50% Orcadian +25% English +25% Spanish @ 3.425491
14 50% HungaryGamba_BA +25% Corded_Ware_LN +25% Spanish_North @ 3.439934
15 50% Orcadian +25% Scottish +25% Spanish @ 3.451739
16 50% Orcadian +25% HungaryGamba_BA +25% Spanish @ 3.470206
17 50% Basque +25% Corded_Ware_LN +25% Orcadian @ 3.489658
18 50% Spanish_North +25% Corded_Ware_LN +25% Icelandic @ 3.496776
19 50% Orcadian +25% Norwegian +25% Spanish @ 3.510492
20 50% Icelandic +25% Icelandic +25% Spanish @ 3.510629
2998878 iterations.

Using 4 populations approximation:
1 Orcadian+Orcadian+Orcadian+Spanish @ 3.222418
2 HungaryGamba_BA+HungaryGamba_BA+Iranian_Jew+Loschb our @ 3.222439
3 HungaryGamba_BA+HungaryGamba_BA+Iraqi_Jew+Loschbou r @ 3.227322
4 HungaryGamba_BA+HungaryGamba_BA+Iranian_Jewish+Los chbour @ 3.253491
5 Corded_Ware_LN+HungaryGamba_BA+HungaryGamba_BA+Spa nish @ 3.253984
6 HungaryGamba_BA+Iranian_Jewish+Loschbour+Spanish_N orth @ 3.285585
7 Corded_Ware_LN+French_South+HungaryGamba_BA+Hungar yGamba_BA @ 3.294261
8 Icelandic+Orcadian+Orcadian+Spanish @ 3.325169
9 Basque+HungaryGamba_BA+Iranian_Jewish+Loschbour @ 3.325271
10 HungaryGamba_BA+HungaryGamba_BA+Iraqi_Mandaean+Los chbour @ 3.348462
11 Basque+Corded_Ware_LN+Orcadian+Spanish @ 3.354916
12 HungaryGamba_BA+Iranian_Jew+Loschbour+Spanish_Nort h @ 3.364963
13 HungaryGamba_BA+Iraqi_Jew+Loschbour+Spanish_North @ 3.365244
14 Corded_Ware_LN+Orcadian+Spanish+Spanish_North @ 3.368243
15 Bell_Beaker_LN+Orcadian+Orcadian+Spanish @ 3.370585
16 Basque+Corded_Ware_LN+HungaryGamba_BA+HungaryGamba _BA @ 3.388769
17 Basque+HungaryGamba_BA+Iraqi_Jew+Loschbour @ 3.393976
18 Basque+Iraqi_Jew+Loschbour+Orcadian @ 3.394412
19 Corded_Ware_LN+Orcadian+Spanish_North+Spanish_Nort h @ 3.402899
20 Basque+Corded_Ware_LN+HungaryGamba_BA+Orcadian @ 3.404468
21 Iraqi_Jew+Loschbour+Orcadian+Spanish_North @ 3.413371
22 Basque+Corded_Ware_LN+Icelandic+Spanish @ 3.414507
23 Basque+HungaryGamba_BA+Iranian_Jew+Loschbour @ 3.418666
24 Icelandic+Icelandic+Orcadian+Spanish @ 3.420409
25 HungaryGamba_BA+Iranian_Jew+Loschbour+Spanish @ 3.42456
26 Corded_Ware_LN+Icelandic+Spanish+Spanish_North @ 3.425298
27 English+Orcadian+Orcadian+Spanish @ 3.425491
28 Basque+Corded_Ware_LN+Orcadian+Spanish_North @ 3.427477
29 Corded_Ware_LN+French_South+Orcadian+Spanish_North @ 3.42991
30 French_South+HungaryGamba_BA+Iraqi_Jew+Loschbour @ 3.436826
31 Corded_Ware_LN+French_South+HungaryGamba_BA+Orcadi an @ 3.437431
32 Corded_Ware_LN+HungaryGamba_BA+HungaryGamba_BA+Spa nish_North @ 3.439934
33 Basque+English+Iraqi_Jew+Loschbour @ 3.441837
34 Orcadian+Orcadian+Scottish+Spanish @ 3.451739
35 Bell_Beaker_LN+Corded_Ware_LN+Spanish+Spanish_Nort h @ 3.458053
36 Basque+Bell_Beaker_LN+Corded_Ware_LN+Spanish @ 3.458915
37 English+Iraqi_Jew+Loschbour+Spanish_North @ 3.459032
38 HungaryGamba_BA+Iraqi_Mandaean+Loschbour+Spanish_N orth @ 3.459593
39 Basque+Corded_Ware_LN+French+HungaryGamba_BA @ 3.460791
40 Basque+Icelandic+Iraqi_Jew+Loschbour @ 3.461338
24935443 iterations.

[J Man]

My K9 Oracle results. The Gaussian method seems to give lower distances for me.

Least-squares method.

Using 1 population approximation:
1 Hungarian @ 2.980116
2 Bosnian @ 5.087637
3 Serbian_Bosnia @ 5.101173
4 Czech @ 5.463776
5 Croatian @ 5.666859
6 Utah_German @ 6.930919
7 English @ 7.468284
8 Ukrainian_Poltava @ 7.601362
9 Scottish @ 7.807748
10 Ukrainian_Lviv @ 8.185614
11 Orcadian @ 8.259132
12 Ukrainian @ 8.914704
13 Norwegian @ 9.546264
14 Serbian @ 9.897679
15 Icelandic @ 10.018153
16 Utah_Scandinavian @ 10.026612
17 Ukrainian_Kharkov @ 10.05651
18 Bell_Beaker_LN @ 11.536292
19 French @ 11.744062
20 Montenegrin @ 11.759133
208 iterations.

Using 2 populations approximation:
1 Belarusian+Romanian @ 1.246407
2 Serbian+Ukrainian @ 1.431155
3 Montenegrin+Russian @ 1.457706
4 Belarusian+Macedonian @ 1.627804
5 Polish+Romanian @ 1.651588
6 Serbian+Ukrainian_Kharkov @ 1.657896
7 Belarusian+Bulgarian @ 1.658239
8 Belarusian+Montenegrin @ 1.72201
9 Serbian+Ukrainian_Lviv @ 1.73219
10 Estonian+Kosovar @ 1.799548
11 Macedonian+Russian @ 1.8152
12 Montenegrin+Ukrainian_Kharkov @ 1.967714
13 Bosnian+Ukrainian_Poltava @ 2.001368
14 Montenegrin+Ukrainian @ 2.015164
15 Serbian+Ukrainian_Poltava @ 2.040575
16 Russian+Serbian @ 2.051831
17 Bulgarian+Polish @ 2.062651
18 Belarusian+Serbian @ 2.114531
19 Romanian+Russian @ 2.116458
20 Romanian+Ukrainian_Kharkov @ 2.125913
21736 iterations.

Using 3 populations approximation:
1 50% Belarusian +25% Ashkenazi_Jew +25% Ukrainian_Kharkov @ 1.037813
2 50% Montenegrin +25% Moksha +25% Ukrainian_Kharkov @ 1.064279
3 50% Bell_Beaker_LN +25% Neolithic_Hungary +25% North_Ossetian @ 1.072151
4 50% Bulgarian +25% Estonian +25% Ukrainian_Kharkov @ 1.07735
5 50% Bell_Beaker_LN +25% Balkar +25% Neolithic_Hungary @ 1.078467
6 50% Utah_Scandinavian +25% Balkar +25% Neolithic_Hungary @ 1.09793
7 50% Ukrainian_Kharkov +25% Russian +25% West_Sicilian @ 1.114795
8 50% Utah_Scandinavian +25% Neolithic_Hungary +25% North_Ossetian @ 1.116012
9 50% Montenegrin +25% Russian +25% Ukrainian_Kharkov @ 1.131236
10 50% Ukrainian_Kharkov +25% Moksha +25% West_Sicilian @ 1.134569
11 50% Ukrainian_Poltava +25% Ashkenazi_Jew +25% Estonian @ 1.137874
12 50% Ukrainian_Kharkov +25% Russian +25% Sicilian @ 1.164264
13 50% Belarusian +25% East_Sicilian +25% Ukrainian_Kharkov @ 1.175789
14 50% Ukrainian_Lviv +25% Ashkenazi_Jew +25% Estonian @ 1.184887
15 50% Belarusian +25% Belarusian +25% South_Italian @ 1.191018
16 50% Ukrainian_Kharkov +25% Greek +25% Ukrainian_Lviv @ 1.193397
17 50% Estonian +25% Ashkenazi_Jew +25% Bosnian @ 1.195438
18 50% Belarusian +25% Belarusian +25% East_Sicilian @ 1.212847
19 50% Russian +25% English +25% Greek @ 1.225724
20 50% Estonian +25% Ashkenazi_Jew +25% Serbian_Bosnia @ 1.23337
1856590 iterations.

Using 4 populations approximation:
1 Balkar+Corded_Ware_LN+Loschbour+Stuttgart @ 0.942921
2 Corded_Ware_LN+Loschbour+North_Ossetian+Stuttgart @ 0.96087
3 Romanian+Russian+Serbian+Ukrainian_Kharkov @ 0.993357
4 HungaryGamba_BA+Motala12+North_Ossetian+West_Sicil ian @ 0.998104
5 Balkar+Bell_Beaker_LN+Neolithic_Hungary+Utah_Scand inavian @ 1.002778
6 Balkar+French+Loschbour+Tuscan @ 1.007526
7 Bell_Beaker_LN+Neolithic_Hungary+North_Ossetian+Ut ah_Scandinavian @ 1.009351
8 French+Loschbour+North_Ossetian+Tuscan @ 1.01158
9 French+Motala12+North_Ossetian+Tuscan @ 1.015804
10 Balkar+HungaryGamba_BA+Motala12+West_Sicilian @ 1.026906
11 Balkar+French+Motala12+Tuscan @ 1.032344
12 Balkar+Corded_Ware_LN+LBK_EN+Loschbour @ 1.036327
13 Ashkenazi_Jew+Belarusian+Belarusian+Ukrainian_Khar kov @ 1.037813
14 Corded_Ware_LN+LBK_EN+Loschbour+North_Ossetian @ 1.052401
15 Estonian+South_Italian+Ukrainian+Ukrainian_Kharkov @ 1.063309
16 Moksha+Montenegrin+Montenegrin+Ukrainian_Kharkov @ 1.064279
17 Balkar+Bell_Beaker_LN+Icelandic+Neolithic_Hungary @ 1.06766
18 Macedonian+Russian+Serbian+Ukrainian_Kharkov @ 1.068992
19 Bell_Beaker_LN+Bell_Beaker_LN+Neolithic_Hungary+No rth_Ossetian @ 1.072151
20 Bell_Beaker_LN+Icelandic+Neolithic_Hungary+North_O ssetian @ 1.07602
21 Bulgarian+Bulgarian+Estonian+Ukrainian_Kharkov @ 1.07735
22 Balkar+Bell_Beaker_LN+Bell_Beaker_LN+Neolithic_Hun gary @ 1.078467
23 Greek+Moksha+Scottish+Ukrainian_Kharkov @ 1.082153
24 Czech+Greek+Russian+Ukrainian_Kharkov @ 1.093773
25 Balkar+HungaryGamba_BA+Loschbour+Sicilian @ 1.094829
26 Balkar+Neolithic_Hungary+Utah_Scandinavian+Utah_Sc andinavian @ 1.09793
27 HungaryGamba_BA+Loschbour+North_Ossetian+Sicilian @ 1.098464
28 Adygei+Macedonian+Motala12+Spanish @ 1.100849
29 Estonian+South_Italian+Ukrainian_Kharkov+Ukrainian _Lviv @ 1.103213
30 Greek+Moksha+Ukrainian_Kharkov+Utah_German @ 1.11121
31 Bulgarian+Russian+Serbian+Ukrainian_Kharkov @ 1.111591
32 Belarusian+East_Sicilian+Russian+Ukrainian_Kharkov @ 1.114541
33 Russian+Ukrainian_Kharkov+Ukrainian_Kharkov+West_S icilian @ 1.114795
34 Macedonian+Motala12+North_Ossetian+Spanish @ 1.115766
35 Neolithic_Hungary+North_Ossetian+Utah_Scandinavian +Utah_Scandinavian @ 1.116012
36 Romanian+Serbian_Bosnia+Ukrainian+Ukrainian_Kharko v @ 1.116367
37 Greek+Moksha+Orcadian+Ukrainian_Kharkov @ 1.117828
38 Ashkenazi_Jew+Estonian+Ukrainian_Lviv+Ukrainian_Po ltava @ 1.12061
39 Adygei+HungaryGamba_BA+Motala12+West_Sicilian @ 1.120708
40 Moksha+Montenegrin+Serbian+Ukrainian_Kharkov @ 1.122215
5463260 iterations.


Gaussian method.
Noise dispersion set to 0.584552

Using 1 population approximation:
1 Serbian_Bosnia @ 0.717519
2 Croatian @ 1.166977
3 Hungarian @ 2.065061
4 Czech @ 2.461401
5 Bosnian @ 3.07512
6 Ukrainian_Poltava @ 3.344542
7 Serbian @ 3.687123
8 Ukrainian_Lviv @ 3.71312
9 English @ 3.718622
10 Montenegrin @ 4.012161
11 Utah_German @ 4.183269
12 Ukrainian @ 4.195605
13 Scottish @ 4.605028
14 Ukrainian_Kharkov @ 4.63527
15 Utah_Scandinavian @ 4.766292
16 Polish @ 4.807265
17 Icelandic @ 4.88771
18 Orcadian @ 4.90091
19 Belarusian @ 5.013392
20 Macedonian @ 5.060371
208 iterations.

Using 2 populations approximation:
1 Lithuanian+Macedonian @ 0.152728
2 Belarusian+Montenegrin @ 0.260411
3 Kosovar+Lithuanian @ 0.268522
4 Croatian+Ukrainian_Poltava @ 0.272737
5 Czech+Serbian_Bosnia @ 0.290687
6 Serbian_Bosnia+Ukrainian_Poltava @ 0.303103
7 Lithuanian+Montenegrin @ 0.314969
8 Montenegrin+Polish @ 0.322683
9 Belarusian+Macedonian @ 0.366691
10 Macedonian+Polish @ 0.459249
11 Croatian+Czech @ 0.466762
12 Serbian_Bosnia+Ukrainian_Lviv @ 0.48232
13 Montenegrin+Ukrainian_Lviv @ 0.489223
14 Croatian+Ukrainian_Kharkov @ 0.552734
15 Montenegrin+Ukrainian_Poltava @ 0.604766
16 Croatian+Ukrainian_Lviv @ 0.685447
17 Serbian+Ukrainian_Kharkov @ 0.700689
18 Croatian+Serbian_Bosnia @ 0.709747
19 Serbian_Bosnia+Serbian_Bosnia @ 0.717519
20 Belarusian+Serbian @ 0.729935
21736 iterations.

Using 3 populations approximation:
1 50% Serbian_Bosnia +25% Lithuanian +25% Montenegrin @ 0.052172
2 50% Croatian +25% Lithuanian +25% Montenegrin @ 0.057238
3 50% Serbian_Bosnia +25% Lithuanian +25% Macedonian @ 0.067082
4 50% Serbian_Bosnia +25% Croatian +25% Lithuanian @ 0.068092
5 50% Serbian_Bosnia +25% Lithuanian +25% Serbian_Bosnia @ 0.068189
6 50% Croatian +25% Lithuanian +25% Macedonian @ 0.069213
7 50% Croatian +25% Lithuanian +25% Serbian_Bosnia @ 0.072996
8 50% Montenegrin +25% Lithuanian +25% Serbian_Bosnia @ 0.074377
9 50% Montenegrin +25% Croatian +25% Lithuanian @ 0.074904
10 50% Neolithic_Hungary +25% Abkhasian +25% Lithuanian @ 0.081151
11 50% Serbian_Bosnia +25% Lithuanian +25% Serbian @ 0.082705
12 50% Croatian +25% Croatian +25% Lithuanian @ 0.084135
13 50% Croatian +25% Lithuanian +25% Serbian @ 0.104041
14 50% Lithuanian +25% Greek +25% Montenegrin @ 0.107316
15 50% Croatian +25% Croatian +25% Ukrainian_Kharkov @ 0.109732
16 50% Montenegrin +25% Lithuanian +25% Ukrainian_Kharkov @ 0.118162
17 50% Montenegrin +25% Czech +25% Lithuanian @ 0.121077
18 50% Serbian_Bosnia +25% Polish +25% Serbian_Bosnia @ 0.121505
19 50% Croatian +25% Serbian_Bosnia +25% Ukrainian_Kharkov @ 0.121786
20 50% Serbian_Bosnia +25% Croatian +25% Polish @ 0.124494
2809743 iterations.

Using 4 populations approximation:
1 Lithuanian+Montenegrin+Serbian_Bosnia+Serbian_Bosn ia @ 0.052172
2 Croatian+Lithuanian+Montenegrin+Serbian_Bosnia @ 0.052673
3 Croatian+Croatian+Lithuanian+Montenegrin @ 0.057238
4 Abkhasian+HungaryGamba_BA+Lithuanian+Neolithic_Hun gary @ 0.064846
5 Georgian+Loschbour+Spain_MN+Ukrainian_Kharkov @ 0.065472
6 Croatian+Lithuanian+Macedonian+Serbian_Bosnia @ 0.065532
7 Lithuanian+Macedonian+Serbian_Bosnia+Serbian_Bosni a @ 0.067082
8 Croatian+Lithuanian+Serbian_Bosnia+Serbian_Bosnia @ 0.068092
9 Lithuanian+Serbian_Bosnia+Serbian_Bosnia+Serbian_B osnia @ 0.068189
10 Croatian+Croatian+Lithuanian+Macedonian @ 0.069213
11 Croatian+Croatian+Lithuanian+Serbian_Bosnia @ 0.072996
12 Lithuanian+Montenegrin+Montenegrin+Serbian_Bosnia @ 0.074377
13 Georgian+HungaryGamba_BA+Loschbour+Montenegrin @ 0.074589
14 Croatian+Lithuanian+Montenegrin+Montenegrin @ 0.074904
15 Abkhasian+Lithuanian+Neolithic_Hungary+Neolithic_H ungary @ 0.081151
16 Lithuanian+Serbian+Serbian_Bosnia+Serbian_Bosnia @ 0.082705
17 Croatian+Croatian+Croatian+Lithuanian @ 0.084135
18 Abkhasian+HungaryGamba_BA+Loschbour+Montenegrin @ 0.089151
19 Croatian+Lithuanian+Serbian+Serbian_Bosnia @ 0.089341
20 Croatian+Kosovar+Lithuanian+Ukrainian_Kharkov @ 0.093547
21 Esperstedt_MN+Georgian+Loschbour+Ukrainian_Kharkov @ 0.094154
22 Lithuanian+Montenegrin+Serbian+Serbian_Bosnia @ 0.099051
23 Kosovar+Lithuanian+Montenegrin+Ukrainian_Kharkov @ 0.10123
24 Abkhasian+HungaryGamba_BA+Kosovar+Loschbour @ 0.10167
25 Croatian+Croatian+Lithuanian+Serbian @ 0.104041
26 Abkhasian+HungaryGamba_BA+Loschbour+Macedonian @ 0.104191
27 Greek+Lithuanian+Lithuanian+Montenegrin @ 0.107316
28 Croatian+Lithuanian+Montenegrin+Serbian @ 0.108314
29 Abkhasian+Loschbour+Spain_MN+Ukrainian_Poltava @ 0.108637
30 Croatian+Croatian+Croatian+Ukrainian_Kharkov @ 0.109732
31 Kosovar+Lithuanian+Serbian_Bosnia+Ukrainian_Kharko v @ 0.112093
32 Georgian+HungaryGamba_BA+Loschbour+Macedonian @ 0.112198
33 Croatian+Lithuanian+Macedonian+Montenegrin @ 0.113952
34 Lithuanian+Macedonian+Montenegrin+Serbian_Bosnia @ 0.115966
35 Lithuanian+Macedonian+Montenegrin+Ukrainian_Kharko v @ 0.116993
36 Lithuanian+Montenegrin+Montenegrin+Ukrainian_Khark ov @ 0.118162
37 Abkhasian+Greek+Loschbour+Neolithic_Hungary @ 0.118366
38 Abkhasian+Loschbour+Spain_MN+Ukrainian_Kharkov @ 0.120524
39 Czech+Lithuanian+Montenegrin+Montenegrin @ 0.121077
40 Polish+Serbian_Bosnia+Serbian_Bosnia+Serbian_Bosni a @ 0.121505
19486066 iterations.

[Radboud]

Nevermind, special thanks to noel!


Least-squares method.

Using 1 population approximation:
1 Czech @ 1.408475
2 Scottish @ 2.677705
3 Utah_German @ 2.679119
4 Orcadian @ 2.805147
5 English @ 3.931419
6 Norwegian @ 4.394439
7 Icelandic @ 4.629303
8 Utah_Scandinavian @ 4.958517
9 Ukrainian_Poltava @ 5.150411
10 Hungarian @ 5.16867
11 Ukrainian_Lviv @ 5.99534
12 Bell_Beaker_LN @ 6.379911
13 Ukrainian_Kharkov @ 7.093429
14 Ukrainian @ 7.373038
15 Polish @ 8.545345
16 Croatian @ 9.03502
17 Serbian_Bosnia @ 9.172202
18 Belarusian @ 9.571635
19 Bosnian @ 9.746154
20 Russian @ 11.506386
209 iterations.

Using 2 populations approximation:
1 Czech+Czech @ 1.408475
2 Hungarian+Icelandic @ 1.496645
3 English+Ukrainian_Poltava @ 1.551627
4 Czech+Utah_German @ 1.590454
5 Czech+Scottish @ 1.615069
6 Hungarian+Utah_Scandinavian @ 1.677442
7 Czech+Orcadian @ 1.704029
8 English+Ukrainian_Lviv @ 1.802945
9 Bell_Beaker_LN+Hungarian @ 1.810191
10 Hungarian+Orcadian @ 1.881452
11 Hungarian+Norwegian @ 1.926415
12 Czech+English @ 1.975282
13 Bell_Beaker_LN+Serbian_Bosnia @ 2.06803
14 Bell_Beaker_LN+Croatian @ 2.099099
15 Orcadian+Utah_German @ 2.21681
16 Ukrainian_Poltava+Utah_German @ 2.229081
17 Belarusian+French @ 2.237897
18 English+Ukrainian @ 2.280943
19 Croatian+Polish @ 2.366101
20 English+Orcadian @ 2.381579
21945 iterations.

Using 3 populations approximation:
1 50% Lithuanian +25% English +25% Tuscan @ 1.110743
2 50% Icelandic +25% Kosovar +25% Lithuanian @ 1.193064
3 50% Lithuanian +25% Bergamo +25% Croatian @ 1.195955
4 50% Icelandic +25% Czech +25% Serbian_Bosnia @ 1.204919
5 50% Lithuanian +25% French +25% Kosovar @ 1.221413
6 50% Orcadian +25% Icelandic +25% Serbian_Bosnia @ 1.225443
7 50% Lithuanian +25% Bergamo +25% Serbian_Bosnia @ 1.226581
8 50% Icelandic +25% Croatian +25% Czech @ 1.243669
9 50% English +25% Lithuanian +25% Serbian @ 1.257711
10 50% HungaryGamba_BA +25% Corded_Ware_LN +25% Hungarian @ 1.267125
11 50% Icelandic +25% Montenegrin +25% Polish @ 1.272769
12 50% Utah_German +25% Lithuanian +25% Montenegrin @ 1.274963
13 50% Orcadian +25% Serbian_Bosnia +25% Utah_Scandinavian @ 1.288863
14 50% Orcadian +25% Orcadian +25% Serbian_Bosnia @ 1.300985
15 50% Lithuanian +25% Tuscan +25% Utah_German @ 1.306626
16 50% Czech +25% Czech +25% English @ 1.318417
17 50% Czech +25% Czech +25% Utah_German @ 1.320558
18 50% Orcadian +25% Czech +25% Hungarian @ 1.321649
19 50% Scottish +25% Lithuanian +25% Macedonian @ 1.326415
20 50% Orcadian +25% Croatian +25% Icelandic @ 1.329892
1796731 iterations.

Using 4 populations approximation:
1 English+Icelandic+Lithuanian+Macedonian @ 1.084367
2 English+Lithuanian+Montenegrin+Orcadian @ 1.091386
3 English+Lithuanian+Lithuanian+Tuscan @ 1.110743
4 English+Lithuanian+Macedonian+Orcadian @ 1.157949
5 Croatian+English+Orcadian+Polish @ 1.158575
6 English+Lithuanian+Montenegrin+Scottish @ 1.167218
7 English+Orcadian+Polish+Serbian_Bosnia @ 1.181426
8 HungaryGamba_BA+Lithuanian+Macedonian+Polish @ 1.184607
9 Bergamo+Lithuanian+Orcadian+Polish @ 1.185602
10 Czech+English+Lithuanian+Montenegrin @ 1.188023
11 Icelandic+Icelandic+Kosovar+Lithuanian @ 1.193064
12 Bergamo+Croatian+Lithuanian+Lithuanian @ 1.195955
13 Czech+Icelandic+Icelandic+Serbian_Bosnia @ 1.204919
14 English+Icelandic+Polish+Serbian_Bosnia @ 1.213599
15 Croatian+English+Icelandic+Polish @ 1.214023
16 Bergamo+Czech+Lithuanian+Polish @ 1.214353
17 Bulgarian+HungaryGamba_BA+Lithuanian+Polish @ 1.216858
18 French+Kosovar+Lithuanian+Lithuanian @ 1.221413
19 Icelandic+Orcadian+Orcadian+Serbian_Bosnia @ 1.225443
20 Bergamo+Lithuanian+Lithuanian+Serbian_Bosnia @ 1.226581
21 English+Lithuanian+Macedonian+Utah_Scandinavian @ 1.23034
22 French+Lithuanian+Montenegrin+Polish @ 1.235384
23 English+Lithuanian+Macedonian+Norwegian @ 1.237425
24 HungaryGamba_BA+Lithuanian+Montenegrin+Ukrainian @ 1.24104
25 English+Lithuanian+Serbian+Utah_German @ 1.242814
26 English+Lithuanian+Montenegrin+Utah_German @ 1.243459
27 Croatian+Czech+Icelandic+Icelandic @ 1.243669
28 HungaryGamba_BA+Lithuanian+Macedonian+Ukrainian @ 1.253703
29 English+English+Lithuanian+Serbian @ 1.257711
30 Corded_Ware_LN+Hungarian+HungaryGamba_BA+HungaryGa mba_BA @ 1.267125
31 Belarusian+HungaryGamba_BA+Lithuanian+Macedonian @ 1.269569
32 Icelandic+Icelandic+Montenegrin+Polish @ 1.272769
33 Lithuanian+Montenegrin+Utah_German+Utah_German @ 1.274963
34 HungaryGamba_BA+Polish+Serbian_Bosnia+Ukrainian @ 1.27713
35 Czech+English+Lithuanian+Serbian @ 1.277562
36 Orcadian+Orcadian+Serbian_Bosnia+Utah_Scandinavian @ 1.288863
37 Croatian+Orcadian+Polish+Utah_German @ 1.298918
38 French+Lithuanian+Polish+Serbian @ 1.300555
39 Lithuanian+Montenegrin+Scottish+Utah_German @ 1.300671
40 Orcadian+Orcadian+Orcadian+Serbian_Bosnia @ 1.300985
5344826 iterations.


Gaussian method.
Noise dispersion set to 0.584552

Using 1 population approximation:
1 Orcadian @ 3.347718
2 English @ 3.634817
3 Icelandic @ 3.70426
4 Czech @ 3.824134
5 Scottish @ 3.871254
6 Utah_German @ 4.070009
7 Bell_Beaker_LN @ 4.162268
8 Norwegian @ 4.238278
9 Utah_Scandinavian @ 4.396865
10 Ukrainian_Poltava @ 4.416185
11 Hungarian @ 4.417646
12 Polish @ 4.48032
13 Croatian @ 4.494352
14 Serbian_Bosnia @ 4.552573
15 HungaryGamba_BA @ 4.562331
16 Ukrainian_Lviv @ 4.640856
17 Ukrainian_Kharkov @ 4.645257
18 Bosnian @ 4.947949
19 Ukrainian @ 4.991282
20 French @ 5.029896
209 iterations.

Using 2 populations approximation:
1 Orcadian+Orcadian @ 3.347718
2 HungaryGamba_BA+Polish @ 3.391364
3 HungaryGamba_BA+Orcadian @ 3.461871
4 English+Orcadian @ 3.476551
5 Icelandic+Orcadian @ 3.53606
6 HungaryGamba_BA+Lithuanian @ 3.586922
7 English+Icelandic @ 3.591506
8 HungaryGamba_BA+Icelandic @ 3.601025
9 Czech+HungaryGamba_BA @ 3.60161
10 Czech+Orcadian @ 3.624868
11 English+English @ 3.634817
12 Orcadian+Scottish @ 3.638715
13 HungaryGamba_BA+Ukrainian_Poltava @ 3.655204
14 Czech+English @ 3.685892
15 Lithuanian+Montenegrin @ 3.694171
16 HungaryGamba_BA+Ukrainian_Lviv @ 3.698018
17 Icelandic+Icelandic @ 3.70426
18 Czech+Icelandic @ 3.731356
19 English+Polish @ 3.733319
20 HungaryGamba_BA+Ukrainian_Kharkov @ 3.736611
21945 iterations.

Using 3 populations approximation:
1 50% HungaryGamba_BA +25% Georgian +25% Loschbour @ 2.876078
2 50% Orcadian +25% HungaryGamba_BA +25% Orcadian @ 3.265413
3 50% HungaryGamba_BA +25% Corded_Ware_LN +25% HungaryGamba_BA @ 3.271264
4 50% Lithuanian +25% HungaryGamba_BA +25% Kosovar @ 3.288777
5 50% HungaryGamba_BA +25% Lithuanian +25% Macedonian @ 3.351156
6 50% Orcadian +25% HungaryGamba_BA +25% Icelandic @ 3.352883
7 50% HungaryGamba_BA +25% Lithuanian +25% Serbian_Bosnia @ 3.355816
8 50% HungaryGamba_BA +25% Lithuanian +25% Montenegrin @ 3.359541
9 50% Orcadian +25% HungaryGamba_BA +25% Polish @ 3.375363
10 50% Lithuanian +25% HungaryGamba_BA +25% Macedonian @ 3.385459
11 50% HungaryGamba_BA +25% Polish +25% Polish @ 3.391364
12 50% HungaryGamba_BA +25% Croatian +25% Lithuanian @ 3.39142
13 50% Orcadian +25% Czech +25% HungaryGamba_BA @ 3.394768
14 50% HungaryGamba_BA +25% Corded_Ware_LN +25% Orcadian @ 3.396561
15 50% Orcadian +25% English +25% HungaryGamba_BA @ 3.399088
16 50% Orcadian +25% English +25% Orcadian @ 3.409021
17 50% HungaryGamba_BA +25% Orcadian +25% Polish @ 3.410474
18 50% Lithuanian +25% Greek +25% HungaryGamba_BA @ 3.414605
19 50% Lithuanian +25% HungaryGamba_BA +25% Montenegrin @ 3.422685
20 50% HungaryGamba_BA +25% Lithuanian +25% Orcadian @ 3.425249
2757141 iterations.

Using 4 populations approximation:
1 Georgian+HungaryGamba_BA+HungaryGamba_BA+Loschbour @ 2.876078
2 Georgian+HungaryGamba_BA+Loschbour+Neolithic_Hunga ry @ 3.103213
3 Georgian+HungaryGamba_BA+Loschbour+Spanish_North @ 3.221195
4 HungaryGamba_BA+Orcadian+Orcadian+Orcadian @ 3.265413
5 Corded_Ware_LN+HungaryGamba_BA+HungaryGamba_BA+Hun garyGamba_BA @ 3.271264
6 Georgian+Lithuanian+Loschbour+Spain_MN @ 3.277747
7 HungaryGamba_BA+Kosovar+Lithuanian+Lithuanian @ 3.288777
8 Esperstedt_MN+Georgian+Lithuanian+Loschbour @ 3.338424
9 Orcadian+Orcadian+Orcadian+Orcadian @ 3.347718
10 HungaryGamba_BA+HungaryGamba_BA+Lithuanian+Macedon ian @ 3.351156
11 HungaryGamba_BA+Icelandic+Orcadian+Orcadian @ 3.352883
12 HungaryGamba_BA+HungaryGamba_BA+Lithuanian+Serbian _Bosnia @ 3.355816
13 Basque+Georgian+HungaryGamba_BA+Loschbour @ 3.357889
14 HungaryGamba_BA+Lithuanian+Macedonian+Orcadian @ 3.358729
15 HungaryGamba_BA+HungaryGamba_BA+Lithuanian+Montene grin @ 3.359541
16 HungaryGamba_BA+Lithuanian+Montenegrin+Orcadian @ 3.367065
17 HungaryGamba_BA+Orcadian+Orcadian+Polish @ 3.375363
18 HungaryGamba_BA+Kosovar+Lithuanian+Polish @ 3.384613
19 HungaryGamba_BA+Lithuanian+Lithuanian+Macedonian @ 3.385459
20 HungaryGamba_BA+Icelandic+Lithuanian+Macedonian @ 3.387676
21 HungaryGamba_BA+HungaryGamba_BA+Polish+Polish @ 3.391364
22 Croatian+HungaryGamba_BA+HungaryGamba_BA+Lithuania n @ 3.39142
23 HungaryGamba_BA+Kosovar+Lithuanian+Orcadian @ 3.392618
24 Czech+HungaryGamba_BA+Orcadian+Orcadian @ 3.394768
25 Corded_Ware_LN+HungaryGamba_BA+HungaryGamba_BA+Orc adian @ 3.396561
26 English+HungaryGamba_BA+Orcadian+Orcadian @ 3.399088
27 HungaryGamba_BA+Icelandic+Lithuanian+Montenegrin @ 3.399251
28 HungaryGamba_BA+Icelandic+Kosovar+Lithuanian @ 3.402889
29 HungaryGamba_BA+Lithuanian+Macedonian+Polish @ 3.403218
30 English+Orcadian+Orcadian+Orcadian @ 3.409021
31 HungaryGamba_BA+Lithuanian+Montenegrin+Polish @ 3.410045
32 English+Georgian+HungaryGamba_BA+Loschbour @ 3.410288
33 HungaryGamba_BA+HungaryGamba_BA+Orcadian+Polish @ 3.410474
34 Greek+HungaryGamba_BA+Lithuanian+Lithuanian @ 3.414605
35 HungaryGamba_BA+Lithuanian+Lithuanian+Montenegrin @ 3.422685
36 English+HungaryGamba_BA+Lithuanian+Montenegrin @ 3.424217
37 HungaryGamba_BA+HungaryGamba_BA+Lithuanian+Orcadia n @ 3.425249
38 English+HungaryGamba_BA+Lithuanian+Macedonian @ 3.427318
39 HungaryGamba_BA+Lithuanian+Orcadian+Serbian_Bosnia @ 3.427788
40 Czech+HungaryGamba_BA+HungaryGamba_BA+Lithuanian @ 3.430701
17676805 iterations.

[SwampThing27]

Least-squares method.

Using 1 population approximation:
1 English @ 2.814375
2 Scottish @ 5.225865
3 Hungarian @ 5.310461
4 Czech @ 6.019018
5 Orcadian @ 6.796819
6 French @ 7.349667
7 Croatian @ 7.434427
8 Norwegian @ 7.723309
9 Serbian_Bosnia @ 8.188917
10 Icelandic @ 8.386232
11 HungaryGamba_BA @ 8.559361
12 Bosnian @ 8.931389
13 Bell_Beaker_LN @ 9.88983
14 Ukrainian_Poltava @ 10.151604
15 Ukrainian_Lviv @ 10.961969
16 Serbian @ 11.79602
17 Ukrainian_Kharkov @ 11.859008
18 Ukrainian @ 12.302771
19 Montenegrin @ 13.384107
20 Polish @ 13.411532
207 iterations.

Using 2 populations approximation:
1 Loschbour+Samaritan @ 1.933329
2 French+Norwegian @ 2.029898
3 French+Orcadian @ 2.117766
4 French+Icelandic @ 2.199483
5 French+Scottish @ 2.374296
6 Bell_Beaker_LN+French @ 2.52302
7 Czech+French @ 2.685647
8 English+English @ 2.814375
9 Lithuanian+Spanish @ 2.915391
10 Estonian+Spanish @ 2.978575
11 French+Ukrainian_Poltava @ 3.067991
12 Bergamo+Lithuanian @ 3.197327
13 French+Ukrainian_Lviv @ 3.268459
14 French+Ukrainian_Kharkov @ 3.274813
15 Hungarian+HungaryGamba_BA @ 3.283452
16 Motala12+Samaritan @ 3.327111
17 English+Hungarian @ 3.370048
18 Bergamo+Estonian @ 3.386585
19 Czech+HungaryGamba_BA @ 3.391636
20 English+French @ 3.488369
21528 iterations.

Using 3 populations approximation:
1 50% French_South +25% Corded_Ware_LN +25% Ukrainian_Kharkov @ 1.518788
2 50% French_South +25% Corded_Ware_LN +25% Ukrainian_Lviv @ 1.551562
3 50% French_South +25% Corded_Ware_LN +25% Ukrainian @ 1.560004
4 50% Sicilian +25% Bell_Beaker_LN +25% Loschbour @ 1.571663
5 50% French_South +25% Corded_Ware_LN +25% Polish @ 1.591722
6 50% French_South +25% Belarusian +25% Corded_Ware_LN @ 1.625195
7 50% French_South +25% Corded_Ware_LN +25% Ukrainian_Poltava @ 1.670261
8 50% Sicilian +25% Icelandic +25% Loschbour @ 1.686456
9 50% Sicilian +25% Loschbour +25% Norwegian @ 1.720345
10 50% West_Sicilian +25% Loschbour +25% Orcadian @ 1.760226
11 50% West_Sicilian +25% Loschbour +25% Scottish @ 1.770001
12 50% French +25% Lebanese_Muslim +25% Loschbour @ 1.797279
13 50% West_Sicilian +25% Loschbour +25% Norwegian @ 1.804845
14 50% French +25% Lebanese +25% Loschbour @ 1.809857
15 50% Scottish +25% Spanish +25% Ukrainian_Kharkov @ 1.83523
16 50% Lithuanian +25% Moroccan_Jew +25% Neolithic_Hungary @ 1.836683
17 50% Bell_Beaker_LN +25% Hungarian +25% Spanish @ 1.838886
18 50% Lithuanian +25% Libyan_Jew +25% Neolithic_Hungary @ 1.843367
19 50% Croatian +25% Libyan_Jew +25% Loschbour @ 1.845645
20 50% Norwegian +25% Czech +25% Spanish @ 1.856853
1992689 iterations.

Using 4 populations approximation:
1 Basque+English+Iranian_Jewish+Loschbour @ 1.316569
2 Basque+Iranian_Jew+Loschbour+Scottish @ 1.337322
3 Icelandic+Lebanese_Muslim+Loschbour+Spanish @ 1.367658
4 Basque+Iranian_Jew+Loschbour+Orcadian @ 1.413665
5 French_South+Iraqi_Jew+Loschbour+Norwegian @ 1.42389
6 Basque+Iraqi_Mandaean+Loschbour+Scottish @ 1.425438
7 Lebanese_Muslim+Loschbour+Norwegian+Spanish @ 1.432976
8 Bell_Beaker_LN+Lebanese_Muslim+Loschbour+Spanish @ 1.440944
9 French+HungaryGamba_BA+Loschbour+Syrian @ 1.460406
10 Lebanese_Muslim+Loschbour+Orcadian+Spanish @ 1.472187
11 French_South+Icelandic+Iraqi_Jew+Loschbour @ 1.475385
12 French_South+Iranian_Jew+Loschbour+Scottish @ 1.478344
13 Basque+Czech+Iranian_Jew+Loschbour @ 1.480613
14 French_South+Iraqi_Jew+Loschbour+Orcadian @ 1.492135
15 Basque+French+Kurdish+Loschbour @ 1.494891
16 Basque+Iraqi_Mandaean+Loschbour+Orcadian @ 1.496553
17 French_South+Iraqi_Jewish+Loschbour+Norwegian @ 1.500487
18 Iranian_Jew+Loschbour+Scottish+Spanish_North @ 1.503511
19 Corded_Ware_LN+French_South+French_South+Ukrainian _Kharkov @ 1.518788
20 Czech+French_South+Loschbour+Syrian @ 1.523823
21 Basque+Czech+Iraqi_Mandaean+Loschbour @ 1.525706
22 Basque+English+Iranian_Jew+Loschbour @ 1.529518
23 French_South+Iraqi_Mandaean+Loschbour+Scottish @ 1.531344
24 French_South+Iraqi_Jewish+Loschbour+Orcadian @ 1.531811
25 Icelandic+Loschbour+Spanish+Syrian @ 1.540015
26 Druze+French_South+Loschbour+Ukrainian @ 1.545188
27 Basque+Iranian_Jew+Loschbour+Norwegian @ 1.54761
28 French_South+Icelandic+Iraqi_Jewish+Loschbour @ 1.55027
29 Corded_Ware_LN+French_South+French_South+Ukrainian _Lviv @ 1.551562
30 Icelandic+Lebanese+Loschbour+Spanish @ 1.553363
31 French_South+Iraqi_Jew+Loschbour+Scottish @ 1.554568
32 Corded_Ware_LN+French_South+French_South+Ukrainian @ 1.560004
33 Iraqi_Mandaean+Loschbour+Scottish+Spanish_North @ 1.562244
34 French_South+Iraqi_Jewish+Loschbour+Scottish @ 1.570271
35 Bell_Beaker_LN+Loschbour+Sicilian+Sicilian @ 1.571663
36 Basque+English+Iraqi_Mandaean+Loschbour @ 1.575121
37 Druze+French_South+Loschbour+Ukrainian_Lviv @ 1.579327
38 Bell_Beaker_LN+French_South+Iraqi_Jew+Loschbour @ 1.591031
39 Bulgarian+Loschbour+Neolithic_Hungary+Syrian @ 1.591569
40 Corded_Ware_LN+French_South+French_South+Polish @ 1.591722
6767005 iterations.


Gaussian method.
Noise dispersion set to 0.584552

Using 1 population approximation:
1 Orcadian @ 4.208313
2 English @ 4.27034
3 French @ 4.425323
4 Scottish @ 4.570837
5 Icelandic @ 4.746287
6 Norwegian @ 4.959557
7 Bell_Beaker_LN @ 5.04877
8 Bosnian @ 5.221253
9 Czech @ 5.268793
10 Hungarian @ 5.583021
11 Serbian_Bosnia @ 5.948762
12 HungaryGamba_BA @ 6.135961
13 Ukrainian_Kharkov @ 6.25571
14 Croatian @ 6.48079
15 Ukrainian_Lviv @ 6.499833
16 Polish @ 6.635009
17 Serbian @ 6.637986
18 Ukrainian_Poltava @ 6.677546
19 Ukrainian @ 6.847449
20 Montenegrin @ 7.239959
207 iterations.

Using 2 populations approximation:
1 Basque+Corded_Ware_LN @ 3.72098
2 French+Orcadian @ 3.783625
3 Loschbour+Samaritan @ 3.816398
4 Corded_Ware_LN+Spanish_North @ 3.852617
5 French+Icelandic @ 3.926608
6 Lithuanian+Spanish @ 3.963427
7 Bell_Beaker_LN+French @ 3.972513
8 Orcadian+Spanish @ 4.01631
9 Polish+Spanish @ 4.043848
10 Icelandic+Spanish @ 4.04896
11 Bosnian+HungaryGamba_BA @ 4.089314
12 Bell_Beaker_LN+Spanish @ 4.090819
13 English+French @ 4.093627
14 Corded_Ware_LN+French_South @ 4.115594
15 French+Scottish @ 4.125112
16 HungaryGamba_BA+Orcadian @ 4.139919
17 French+Norwegian @ 4.158633
18 Corded_Ware_LN+Spain_MN @ 4.186074
19 English+Orcadian @ 4.197019
20 Orcadian+Orcadian @ 4.208313
21528 iterations.

Using 3 populations approximation:
1 50% Orcadian +25% Orcadian +25% Spanish @ 3.222418
2 50% HungaryGamba_BA +25% Iranian_Jew +25% Loschbour @ 3.222439
3 50% HungaryGamba_BA +25% Iraqi_Jew +25% Loschbour @ 3.227322
4 50% HungaryGamba_BA +25% Iranian_Jewish +25% Loschbour @ 3.253491
5 50% HungaryGamba_BA +25% Corded_Ware_LN +25% Spanish @ 3.253984
6 50% HungaryGamba_BA +25% Corded_Ware_LN +25% French_South @ 3.294261
7 50% Orcadian +25% Icelandic +25% Spanish @ 3.325169
8 50% HungaryGamba_BA +25% Iraqi_Mandaean +25% Loschbour @ 3.348462
9 50% Orcadian +25% Bell_Beaker_LN +25% Spanish @ 3.370585
10 50% HungaryGamba_BA +25% Basque +25% Corded_Ware_LN @ 3.388769
11 50% Spanish_North +25% Corded_Ware_LN +25% Orcadian @ 3.402899
12 50% Icelandic +25% Orcadian +25% Spanish @ 3.420409
13 50% Orcadian +25% English +25% Spanish @ 3.425491
14 50% HungaryGamba_BA +25% Corded_Ware_LN +25% Spanish_North @ 3.439934
15 50% Orcadian +25% Scottish +25% Spanish @ 3.451739
16 50% Orcadian +25% HungaryGamba_BA +25% Spanish @ 3.470206
17 50% Basque +25% Corded_Ware_LN +25% Orcadian @ 3.489658
18 50% Spanish_North +25% Corded_Ware_LN +25% Icelandic @ 3.496776
19 50% Orcadian +25% Norwegian +25% Spanish @ 3.510492
20 50% Icelandic +25% Icelandic +25% Spanish @ 3.510629
2998878 iterations.

Using 4 populations approximation:
1 Orcadian+Orcadian+Orcadian+Spanish @ 3.222418
2 HungaryGamba_BA+HungaryGamba_BA+Iranian_Jew+Loschb our @ 3.222439
3 HungaryGamba_BA+HungaryGamba_BA+Iraqi_Jew+Loschbou r @ 3.227322
4 HungaryGamba_BA+HungaryGamba_BA+Iranian_Jewish+Los chbour @ 3.253491
5 Corded_Ware_LN+HungaryGamba_BA+HungaryGamba_BA+Spa nish @ 3.253984
6 HungaryGamba_BA+Iranian_Jewish+Loschbour+Spanish_N orth @ 3.285585
7 Corded_Ware_LN+French_South+HungaryGamba_BA+Hungar yGamba_BA @ 3.294261
8 Icelandic+Orcadian+Orcadian+Spanish @ 3.325169
9 Basque+HungaryGamba_BA+Iranian_Jewish+Loschbour @ 3.325271
10 HungaryGamba_BA+HungaryGamba_BA+Iraqi_Mandaean+Los chbour @ 3.348462
11 Basque+Corded_Ware_LN+Orcadian+Spanish @ 3.354916
12 HungaryGamba_BA+Iranian_Jew+Loschbour+Spanish_Nort h @ 3.364963
13 HungaryGamba_BA+Iraqi_Jew+Loschbour+Spanish_North @ 3.365244
14 Corded_Ware_LN+Orcadian+Spanish+Spanish_North @ 3.368243
15 Bell_Beaker_LN+Orcadian+Orcadian+Spanish @ 3.370585
16 Basque+Corded_Ware_LN+HungaryGamba_BA+HungaryGamba _BA @ 3.388769
17 Basque+HungaryGamba_BA+Iraqi_Jew+Loschbour @ 3.393976
18 Basque+Iraqi_Jew+Loschbour+Orcadian @ 3.394412
19 Corded_Ware_LN+Orcadian+Spanish_North+Spanish_Nort h @ 3.402899
20 Basque+Corded_Ware_LN+HungaryGamba_BA+Orcadian @ 3.404468
21 Iraqi_Jew+Loschbour+Orcadian+Spanish_North @ 3.413371
22 Basque+Corded_Ware_LN+Icelandic+Spanish @ 3.414507
23 Basque+HungaryGamba_BA+Iranian_Jew+Loschbour @ 3.418666
24 Icelandic+Icelandic+Orcadian+Spanish @ 3.420409
25 HungaryGamba_BA+Iranian_Jew+Loschbour+Spanish @ 3.42456
26 Corded_Ware_LN+Icelandic+Spanish+Spanish_North @ 3.425298
27 English+Orcadian+Orcadian+Spanish @ 3.425491
28 Basque+Corded_Ware_LN+Orcadian+Spanish_North @ 3.427477
29 Corded_Ware_LN+French_South+Orcadian+Spanish_North @ 3.42991
30 French_South+HungaryGamba_BA+Iraqi_Jew+Loschbour @ 3.436826
31 Corded_Ware_LN+French_South+HungaryGamba_BA+Orcadi an @ 3.437431
32 Corded_Ware_LN+HungaryGamba_BA+HungaryGamba_BA+Spa nish_North @ 3.439934
33 Basque+English+Iraqi_Jew+Loschbour @ 3.441837
34 Orcadian+Orcadian+Scottish+Spanish @ 3.451739
35 Bell_Beaker_LN+Corded_Ware_LN+Spanish+Spanish_Nort h @ 3.458053
36 Basque+Bell_Beaker_LN+Corded_Ware_LN+Spanish @ 3.458915
37 English+Iraqi_Jew+Loschbour+Spanish_North @ 3.459032
38 HungaryGamba_BA+Iraqi_Mandaean+Loschbour+Spanish_N orth @ 3.459593
39 Basque+Corded_Ware_LN+French+HungaryGamba_BA @ 3.460791
40 Basque+Icelandic+Iraqi_Jew+Loschbour @ 3.461338
24935443 iterations.


Interesting oracle results for myself on this one.

[J Man]

I find it a bit strange that everyone else seems to be getting lower (closer) overall genetic distance scores with populations on the Least-squares method and I seem to be the only one who is getting lower (closer) overall genetic distance scores with populations on the Gaussian method.

[Rukha]

Updated oracle, thanks again to noel


Least-squares method.

Using 1 population approximation:
1 Afghan_Pashtun @ 6.278415
2 Tajik_Pomiri @ 10.085386
3 Brahui @ 11.496703
4 Pathan @ 11.534167
5 Balochi @ 12.259532
6 Kalash @ 13.980384
7 Tadjik @ 14.533479
8 Burusho @ 14.755411
9 Afghan_Tadjik @ 17.247026
10 Afghan_Uzbeki @ 17.325523
11 GujaratiA @ 25.394396
12 Lezgin @ 25.748323
13 Chechen @ 26.436329
14 Kumyk @ 27.321175
15 Adygei @ 28.60525
16 Turkmen @ 28.644151
17 Balkar @ 28.81289
18 North_Ossetian @ 28.827934
19 Nogay @ 30.88739
20 Iranian @ 31.15139
209 iterations.

Using 2 populations approximation:
1 Balochi+Tajik_Pomiri @ 2.516468
2 GujaratiA+Lezgin @ 3.071512
3 Brahui+Tajik_Pomiri @ 3.664634
4 Pathan+Tajik_Pomiri @ 3.981992
5 Chechen+GujaratiA @ 4.472687
6 GujaratiB+Lezgin @ 5.193307
7 Kalash+Tadjik @ 5.440438
8 Chechen+GujaratiB @ 6.102733
9 Afghan_Pashtun+Pathan @ 6.138832
10 Adygei+GujaratiA @ 6.187835
11 Pathan+Tadjik @ 6.188728
12 Afghan_Pashtun+Afghan_Pashtun @ 6.278415
13 Afghan_Pashtun+Kalash @ 6.298234
14 GujaratiA+North_Ossetian @ 6.545785
15 Brahmin_UP+Lezgin @ 6.567565
16 Balkar+GujaratiA @ 6.597461
17 Afghan_Pashtun+Tajik_Pomiri @ 6.643455
18 Kalash+Tajik_Pomiri @ 6.713637
19 Afghan_Pashtun+Balochi @ 7.035277
20 Afghan_Pashtun+Brahui @ 7.042316
21945 iterations.

Using 3 populations approximation:
1 50% Tajik_Pomiri +25% Brahui +25% Pathan @ 1.907386
2 50% Tajik_Pomiri +25% Balochi +25% Pathan @ 1.932103
3 50% Balochi +25% Tajik_Pomiri +25% Tajik_Pomiri @ 2.516468
4 50% Pathan +25% Lezgin +25% Tajik_Pomiri @ 2.705162
5 50% Balochi +25% Balochi +25% Yamnaya @ 2.82728
6 50% Lezgin +25% Kalash +25% Muslim_India @ 2.836271
7 50% Lezgin +25% Kalash +25% Punjabi @ 2.88506
8 50% Lezgin +25% Dharkar +25% Kalash @ 2.894434
9 50% Tajik_Pomiri +25% Balochi +25% Brahui @ 2.936495
10 50% Lezgin +25% Kalash +25% Kanjar @ 3.018411
11 50% GujaratiA +25% Lezgin +25% Lezgin @ 3.071512
12 50% Tajik_Pomiri +25% Brahui +25% Kalash @ 3.089544
13 50% Chechen +25% GujaratiC +25% Kalash @ 3.129188
14 50% Lezgin +25% Kalash +25% Kshatriya @ 3.138221
15 50% Pathan +25% Chechen +25% Kalash @ 3.144761
16 50% Pathan +25% Afghan_Pashtun +25% Lezgin @ 3.165672
17 50% Tajik_Pomiri +25% Balochi +25% Kalash @ 3.180108
18 50% Lezgin +25% GujaratiC +25% Kalash @ 3.192067
19 50% Pathan +25% Chechen +25% Tajik_Pomiri @ 3.199231
20 50% Balochi +25% Brahui +25% Yamnaya @ 3.271161
2653163 iterations.

Using 4 populations approximation:
1 Adygei+GujaratiA+Kalash+Tajik_Pomiri @ 1.761004
2 Brahui+Pathan+Tajik_Pomiri+Tajik_Pomiri @ 1.907386
3 Balochi+Pathan+Tajik_Pomiri+Tajik_Pomiri @ 1.932103
4 GujaratiA+Kalash+North_Ossetian+Tajik_Pomiri @ 2.044986
5 Balkar+GujaratiA+Kalash+Tajik_Pomiri @ 2.054142
6 GujaratiA+Kalash+Kumyk+Tajik_Pomiri @ 2.082153
7 Chechen+GujaratiA+Kalash+Tajik_Pomiri @ 2.117782
8 Adygei+GujaratiB+Kalash+Tajik_Pomiri @ 2.29834
9 Balochi+GujaratiA+Lezgin+Tajik_Pomiri @ 2.309555
10 GujaratiA+Kalash+Lezgin+Tadjik @ 2.362811
11 Afghan_Pashtun+Chechen+GujaratiA+Kalash @ 2.372059
12 GujaratiA+Lezgin+Pathan+Tajik_Pomiri @ 2.478541
13 Balochi+Balochi+Tajik_Pomiri+Tajik_Pomiri @ 2.516468
14 Chechen+GujaratiB+Kalash+Tajik_Pomiri @ 2.535778
15 GujaratiB+Kalash+North_Ossetian+Tajik_Pomiri @ 2.540676
16 Balkar+GujaratiB+Kalash+Tajik_Pomiri @ 2.555077
17 GujaratiA+Kalash+Lezgin+Tajik_Pomiri @ 2.571754
18 Afghan_Pashtun+GujaratiA+Kalash+Lezgin @ 2.645416
19 Chechen+GujaratiA+Kalash+Tadjik @ 2.662897
20 Lezgin+Pathan+Pathan+Tajik_Pomiri @ 2.705162
21 GujaratiB+Kalash+Lezgin+Tadjik @ 2.708047
22 Brahui+GujaratiA+Lezgin+Tajik_Pomiri @ 2.765825
23 Adygei+Brahmin_UP+Kalash+Tajik_Pomiri @ 2.796721
24 Balochi+Balochi+Balochi+Yamnaya @ 2.82728
25 Kalash+Lezgin+Lezgin+Muslim_India @ 2.836271
26 Kalash+Lezgin+Lezgin+Punjabi @ 2.88506
27 Dharkar+Kalash+Lezgin+Lezgin @ 2.894434
28 Brahui+GujaratiB+Lezgin+Tajik_Pomiri @ 2.930438
29 Balochi+Brahui+Tajik_Pomiri+Tajik_Pomiri @ 2.936495
30 GujaratiB+Kalash+Lezgin+Tajik_Pomiri @ 2.93829
31 Balochi+Chechen+GujaratiA+Tajik_Pomiri @ 2.93979
32 GujaratiB+Kalash+Kumyk+Tajik_Pomiri @ 2.954371
33 Chechen+GujaratiB+Kalash+Tadjik @ 2.960946
34 Adygei+Afghan_Pashtun+GujaratiA+Kalash @ 2.976472
35 Chechen+Kalash+Lezgin+Muslim_India @ 2.984272
36 Afghan_Pashtun+GujaratiB+Lezgin+Tajik_Pomiri @ 2.997796
37 Abkhasian+Balochi+Velamas+Yamnaya @ 3.000422
38 Chechen+GujaratiC+Kalash+Lezgin @ 3.01571
39 Kalash+Kanjar+Lezgin+Lezgin @ 3.018411
40 Burusho+Chechen+Kalash+Pathan @ 3.029789
13080727 iterations.


Gaussian method.
Noise dispersion set to 0.584552

Using 1 population approximation:
1 Pathan @ 5.596922
2 Tajik_Pomiri @ 6.707238
3 Afghan_Pashtun @ 7.139673
4 Balochi @ 9.458926
5 Brahui @ 9.623752
6 Tadjik @ 9.738789
7 Burusho @ 9.751873
8 Afghan_Tadjik @ 10.904196
9 GujaratiA @ 10.964395
10 Afghan_Uzbeki @ 10.966816
11 Brahmin_UP @ 15.360754
12 Turkmen @ 15.588546
13 GujaratiB @ 15.878578
14 Uzbek @ 16.12673
15 Afghan_Turkmen @ 16.598564
16 Iranian @ 16.767593
17 Kshatriya @ 16.926714
18 Uzbeki @ 17.37159
19 Brahmin_TN @ 17.66315
20 Kurdish @ 18.349951
209 iterations.

Using 2 populations approximation:
1 GujaratiA+Lezgin @ 3.842249
2 Pathan+Tajik_Pomiri @ 4.382191
3 GujaratiB+Lezgin @ 4.433343
4 Chechen+GujaratiA @ 4.514795
5 Balochi+Tajik_Pomiri @ 4.577185
6 Brahmin_UP+Lezgin @ 4.787154
7 Chechen+GujaratiB @ 4.898624
8 Kshatriya+Lezgin @ 5.064396
9 Lezgin+Pathan @ 5.214864
10 Brahmin_TN+Lezgin @ 5.33803
11 Brahmin_UP+Chechen @ 5.392967
12 Pathan+Pathan @ 5.596922
13 GujaratiC+Lezgin @ 5.625661
14 Chechen+Kshatriya @ 5.629023
15 Brahui+Tajik_Pomiri @ 5.663449
16 Chechen+Pathan @ 5.709446
17 Adygei+GujaratiA @ 5.823238
18 Brahmin_TN+Chechen @ 5.863897
19 Afghan_Pashtun+Pathan @ 5.952144
20 GujaratiA+Tajik_Pomiri @ 5.985193
21945 iterations.

Using 3 populations approximation:
1 50% Pathan +25% Kalash +25% Lezgin @ 3.504352
2 50% Pathan +25% Chechen +25% Kalash @ 3.630756
3 50% Pathan +25% Lezgin +25% Pathan @ 3.718745
4 50% Balochi +25% Pathan +25% Yamnaya @ 3.79179
5 50% Balochi +25% Balochi +25% Yamnaya @ 3.827843
6 50% GujaratiA +25% Lezgin +25% Lezgin @ 3.842249
7 50% Kalash +25% Kalash +25% Kosovar @ 3.919549
8 50% Kalash +25% Chechen +25% Pathan @ 3.960015
9 50% Lezgin +25% GujaratiC +25% Kalash @ 3.973171
10 50% Lezgin +25% Kalash +25% Kshatriya @ 3.97356
11 50% Lezgin +25% Brahmin_UP +25% Kalash @ 3.980856
12 50% Pathan +25% Lezgin +25% Tajik_Pomiri @ 3.980939
13 50% Kalash +25% Greek +25% Kalash @ 3.987271
14 50% Pathan +25% Chechen +25% Pathan @ 3.997092
15 50% Lezgin +25% GujaratiB +25% Kalash @ 4.020919
16 50% Pathan +25% GujaratiA +25% Lezgin @ 4.0517
17 50% Lezgin +25% GujaratiA +25% GujaratiB @ 4.055361
18 50% Kalash +25% Kalash +25% Romanian @ 4.058188
19 50% Kalash +25% Lezgin +25% Pathan @ 4.069676
20 50% Kalash +25% Bulgarian +25% Kalash @ 4.07337
4016017 iterations.

Using 4 populations approximation:
1 Kalash+Lezgin+Pathan+Pathan @ 3.504352
2 Chechen+Kalash+Pathan+Pathan @ 3.630756
3 GujaratiA+Kalash+Lezgin+Tajik_Pomiri @ 3.636666
4 Lezgin+Pathan+Pathan+Pathan @ 3.718745
5 GujaratiA+Lezgin+Pathan+Tajik_Pomiri @ 3.725357
6 GujaratiA+Kalash+Lezgin+Pathan @ 3.789246
7 Balochi+Balochi+Pathan+Yamnaya @ 3.79179
8 Chechen+GujaratiA+Kalash+Tajik_Pomiri @ 3.798116
9 GujaratiB+Kalash+Lezgin+Tajik_Pomiri @ 3.811736
10 Balochi+Balochi+Balochi+Yamnaya @ 3.827843
11 GujaratiA+GujaratiA+Lezgin+Lezgin @ 3.842249
12 Chechen+GujaratiA+Kalash+Pathan @ 3.852542
13 Georgian+GujaratiA+Kalash+Tajik_Pomiri @ 3.904197
14 Kalash+Kalash+Kalash+Kosovar @ 3.919549
15 Chechen+GujaratiB+Kalash+Tajik_Pomiri @ 3.926468
16 Brahmin_UP+Kalash+Lezgin+Tajik_Pomiri @ 3.93505
17 Chechen+Kalash+Kalash+Pathan @ 3.960015
18 GujaratiB+Lezgin+Pathan+Tajik_Pomiri @ 3.966917
19 GujaratiC+Kalash+Lezgin+Lezgin @ 3.973171
20 Kalash+Kshatriya+Lezgin+Lezgin @ 3.97356
21 Brahmin_UP+Kalash+Lezgin+Lezgin @ 3.980856
22 Lezgin+Pathan+Pathan+Tajik_Pomiri @ 3.980939
23 Greek+Kalash+Kalash+Kalash @ 3.987271
24 Brahmin_TN+Georgian+Kalash+Yamnaya @ 3.988313
25 Chechen+Pathan+Pathan+Pathan @ 3.997092
26 GujaratiB+Kalash+Lezgin+Lezgin @ 4.020919
27 Brahmin_TN+Georgian+Pathan+Yamnaya @ 4.024065
28 Kalash+Lezgin+Pathan+Tajik_Pomiri @ 4.046328
29 Chechen+GujaratiA+Pathan+Tajik_Pomiri @ 4.049919
30 GujaratiA+Lezgin+Pathan+Pathan @ 4.0517
31 GujaratiA+GujaratiB+Lezgin+Lezgin @ 4.055361
32 Kalash+Kalash+Kalash+Romanian @ 4.058188
33 Kalash+Kalash+Lezgin+Pathan @ 4.069676
34 Kalash+Kshatriya+Lezgin+Tajik_Pomiri @ 4.072278
35 Bulgarian+Kalash+Kalash+Kalash @ 4.07337
36 Balochi+GujaratiA+Lezgin+Tajik_Pomiri @ 4.074707
37 Georgian+GujaratiB+Kalash+Tajik_Pomiri @ 4.084745
38 Brahmin_UP+Chechen+Kalash+Tajik_Pomiri @ 4.088777
39 GujaratiA+GujaratiA+Lezgin+Tajik_Pomiri @ 4.095637
40 Abkhasian+GujaratiA+Kalash+Tajik_Pomiri @ 4.099412
54271909 iterations.

[SwampThing27]

I find it a bit strange that everyone else seems to be getting lower (closer) overall genetic distance scores with populations on the Least-squares method and I seem to be the only one who is getting lower (closer) overall genetic distance scores with populations on the Gaussian method.

A member on another forum swears that the Gaussian method is more accurate than the least squares method. My stats knowledge is limited, so I honestly don't even know the difference.

[J Man]

A member on another forum swears that the Gaussian method is more accurate than the least squares method. My stats knowledge is limited, so I honestly don't even know the difference.

Neither do I to be honest.

[thrax]

Hello everyone. Here are my results:
Oceanian 0.004545
Siberian 0.004615
Sub-Saharan 0.00001
East_Asian 0.003468
Central_Asian 0.250223
South_Asian 0.00001
Amerindian 0.002362
EEF 0.460614
European 0.274152

[email protected] 2,04264201252969
[email protected] 3,40925866399948
[email protected] 5,35144214156968
[email protected] 6,51266499757396
[email protected] 6,51337823234959
[email protected] 8,89696768809324
[email protected] 9,60941436703334
[email protected] 10,7352065218419
[email protected] 10,8265874642382
[email protected] 11,2390069878281
[email protected] 11,3325625834225
[email protected] 11,804966931021
[email protected] 12,4383432945883
[email protected] 12,5185573928047
[email protected] 14,7033714430707
[email protected] 16,506506423906
[email protected] 17,1597774148862
[email protected] 17,7549417294467
[email protected] 19,8228173514838
[email protected] 20,1790212589434

[tamilgangster]

https://docs.google.com/spreadsheets/d/1q_rkm8UwyE0KOpyEzqAmAIeFh7cMUipvDPwqqcEONQM/edit#gid=962519559

Very close to Harappa S-Indian but that had more ENF:

23.65% ANE
22.01% ASE
0.06% WHG-UHG
9.03% East_Eurasian
0.70% West_African
5.54% East_African
39.01% ENF

This was in K7 though.

I'm surprised this component is registering so highly in South Asians

These results make no sense at all, there is something off about the calculation. The south Indian component on harappa DNA was around 50 percent caucasian 50 percent SE asian. This means that The south eurasian and east eurasian combined should be 50% and 50% EEF+ASE. Also the ratio of east and west eurasian in the south indian component may not have the same consistant ratio in every population

[Chad Rohlfsen]

Here's mine. Would someone run the Oracle for me, please? Thanks!

Oceanian 1E-005
European 0.518274
EEF 0.314541
East_Asian 1E-005
South_Asian 1E-005
Central Asian 0.151058
Amerindian 1E-005
Siberian 0.016077
Sub-Saharan 1E-005

[ashwinb]

Here's mine. Can someone run the Oracle for me.
South Asian 71.86%
Caucasus 18.00%
Southwest Asian -
North Amerindian + Arctic 0.14%
Siberian 1.88%
Mediterranean -
East Asian 0.25%
West African 0.45%
North European 7.42%

[MonkeyDLuffy]

Here's mine. Can someone run the Oracle for me.
South Asian 71.86%
Caucasus 18.00%
Southwest Asian -
North Amerindian + Arctic 0.14%
Siberian 1.88%
Mediterranean -
East Asian 0.25%
West African 0.45%
North European 7.42%

This is different k9, you will have to ask david for this, have you already got the k8 results from him?

[ashwinb]

This is different k9, you will have to ask david for this, have you already got the k8 results from him?

Ohh..I messed up. How did you get them? I'll get it from him. Did you email him?

[MonkeyDLuffy]

Ohh..I messed up. How did you get them? I'll get it from him. Did you email him?

You'll have to pay 10 bucks for k8+k6+K9

Email him first and then make the payment

[Longbowman]

$20, is it it not? I paid $20. Either way, best $20 I ever did spend.

[ashwinb]

So finally here's mine:
K9

East_Asian 1E-005
Siberian 0.005678
Sub-Saharan 1E-005
Oceanian 0.009891
Central_Asian 0.309863
South_Asian 0.601221
Amerindian 0.009746
European 0.044162
EEF 0.01942

[Longbowman]

So finally here's mine:
K9

East_Asian 1E-005
Siberian 0.005678
Sub-Saharan 1E-005
Oceanian 0.009891
Central_Asian 0.309863
South_Asian 0.601221
Amerindian 0.009746
European 0.044162
EEF 0.01942

I take it you're Indian, perhaps Telugu or Tamil?

[ashwinb]

I take it you're Indian, perhaps Telugu or Tamil?

I am an indian, from western india, half maharashtrian, half gujarati.My results are fairly similar to some tamil communities (iyengar brahmins) who are supposed to have origins in western india.

[Anglecynn]

deleted

[anglesqueville]

My results:
0,001 oceanian
12,465 central_asian
46,6532 european
0,9251 amerindian
0,001 south_asian
39,0144 EEF
0,001 east_asian
0,647 siberian
0,001 sub_saharan

Oracles (only the best 4-ancestors):
LS: 1 Estonian+HungaryGamba_BA+LBK_EN+Ukrainian_Poltava @ 0,644586 ( a little more eastern-oriented than usual)
Gaussian: Esperstedt_MN+HungaryGamba_BA+Icelandic+Orcadian @ 1,415639 ( as usual, a neolithised proto-celt / north-european )

My mother:
0,001 oceanian
12,7944 central_asian
48,7944 european
0,8117 amerindian
0,001 south_asian
37,8882 EEF
0,001 east_asian
0,3255 siberian
0,001 sub_saharan

her oracles:
LS: 1 Bell_Beaker_LN+English+Orcadian+Spain_MN @ 0,616292 ( rather usual)
gaussian: 1 HungaryGamba_BA+HungaryGamba_BA+HungaryGamba_BA+Hu ngaryGamba_BA @ 1,908971
( my old mother is a bronze age hungarian :biggrin1:)

When I send her oracle-results, I use to take only modern populations ( she's not from bronze age, but she's old):
me :
LS: Sardinian+Scottish+Scottish+Scottish @ 0,797338
gauss: Orcadian+Orcadian+Orcadian+Sardinian @ 2,452703

her:
LS: Icelandic+Icelandic+Icelandic+Sardinian @ 0,82888
gauss: Orcadian+Orcadian+Orcadian+Sardinian @ 2,801478

[Shuffle]

My result, probably looking french again, South-German though:


East_Asian Siberian Sub-Saharan Oceanian Central_Asian South_Asian Amerindian European EEF
0.00001 0.00001 0.00001 0.008214 0.144522 0.013438 0.005063 0.463415 0.365317


Oracle:

66 French 1.92510568
47 Croatian 6.98224838
79 HungaryGamba_BA 7.044282648
59 English 7.180236457
78 Hungarian 8.024918144
164 Serbian_Bosnia 8.235890658
32 Bosnian 9.288129305
163 Serbian 9.391891197

[nee4speed111]

Pop K9
European 0.00001
Central_Asian 0.218484
Amerindian 0.003242
Oceanian 0.010728
Siberian 0.005916
South_Asian 0.028054
East_Asian 0.003959
EEF 0.643993
Sub-Saharan 0.085612

[Anath]

South Asian 0.08
Caucasus 5.63
Southwest Asian 1.55
North Amerindian + Arctic 1.05
Siberian -
Mediterranean 22.81
East Asian -
West African 0.24
North European 68.64

[Edward J]

Father:
South Asian 0.90
Caucasus 8.04
Southwest Asian -
North Amerindian + Arctic 1.12
Siberian -
Mediterranean 26.85
East Asian -
West African 0.57
North European 62.53

[Edward J]

Me:

Population
South Asian 0.21
Caucasus 13.81
Southwest Asian 4.34
North Amerindian + Arctic 0.22
Siberian -
Mediterranean 29.91
East Asian -
West African 0.75
North European 50.7

[XooR]

ME
Eurogenes K9 Admixture Proportions
Population

South Asian -
Caucasus 66.14
Southwest Asian 12.07
North Amerindian + Arctic -
Siberian -
Mediterranean 18.15
East Asian -
West African -
North European 3.64

[Macura]

Eurogenes K9
North European 57.27
Mediterranean 22.80
Caucasus 13.67
Southwest Asian 4.75
South Asian 0.83
East Asian 0.69
West African -
North Amerindian + Arctic -
Siberian -

[The_Lyonnist]

North European 52.82
Mediterranean 32.85
Caucasus 9.49
Southwest Asian 3.69
North Amerindian + Arctic 1.15

[nee4speed111]

Pop K9
European 0.00001
Central_Asian 0.218484
Amerindian 0.003242
Oceanian 0.010728
Siberian 0.005916
South_Asian 0.028054
East_Asian 0.003959
EEF 0.643993
Sub-Saharan 0.085612

Oracle results

[email protected] 9.66803149776077
[email protected] 10.1555134725783
[email protected] 10.7852721420847
[email protected] 12.5462814502943
[email protected] 13.4095223890264
[email protected] 13.7657906891958
[email protected] 14.3989862543244
[email protected] 16.3700320978598
[email protected] 17.2403540573802
[email protected] 17.2969525867073
[email protected] 17.6906084975811
[email protected] 17.7891136729303
[email protected] 17.7897573224657
[email protected] 17.8851655462366
[email protected] 17.8942245459227
[email protected] 18.3266586841794
[email protected] 18.6490715982245
[email protected] 19.9919229765319
[email protected] 20.2880243957004
[email protected] 22.1938805108588