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redifflal
10-22-2014, 02:47 PM
Hello all, I'm a new member on here. I joined Biodiversity forum originally in order to discuss my results, but I don't think there are a lot of people that are very knowledgeable on South Asian genetics (at least not active anymore). I am unfortunately still not that well-informed and the whole subject seems like such a political football that I don't know which source to trust. So this is my result.

2777

So to reiterate the attachment, these are my results:
Y-DNA: R-PF7510 (when I transferred to FTDNA, they said R-F813. Are Geno and FTDNA disagreeing or are they same terms?)
MTDNA: M52'58 (same on FTDNA)
Autosomal breakdown:
55% Southwest Asian
25% Southeast Asian
11% Mediterranean
6% Northern European
2% Northeast Asian

Also, I scored 2.4% Neanderthal and 3.6% Denisovan (6% non-human? Wow)

Father's side's ancestral home is in Pratapgarh, Uttar Pradesh (north-central India/Hindi-heartland) and Kayastha by jaati which is a Kshatriya/Brahmin dual caste. Mother's side ancestral home is in Uttarpara, West Bengal (east India) and Brahmin caste.
These are where my 2 sides of family are from (we're pretty much like the first generation that grew up in the 90s in urban middle-class India who were products of accepted love-marriage across caste and ethnic lines, woohoo liberal India)
http://upload.wikimedia.org/wikipedia/commons/thumb/f/f2/Uttar_Pradesh_district_location_map_Pratapgarh.svg/2000px-Uttar_Pradesh_district_location_map_Pratapgarh.svg .png
http://upload.wikimedia.org/wikipedia/commons/3/3b/India-Kolkata-locator-map.PNG



What does strike me though is the explanations for the autosomal ancestries for all 4 Indian populations on Genographic. They all say the SW Asian component shows the first OOA migrants that populated India. The SE Asian component shows the Austro-Asiatic speaking rice-farmers that spread westward from Northeast India/SE-Asia region. The Mediterranean came with the Neolithic Middle-Eastern farmers (Dravidians?), and the Northern European came with the Indo-European speaking warriors. There is no mention of the Northeast Asian, which surprises me because their sampled North Indian population averages 26% Northeast Asian. Did they sample Ladakhis or Hazaras for North Indians? It seems like in their sampled populations for the 4 Indian populations, the component that stands out most for North Indians against the 3 other Indian regions is the NE-Asian, not the Mediterranean or Northern-European.

So, how long have all my ancestors been in India, with particular emphasis on the Y-chromosome, been in India? I can tell by mtDNA and autosomally, I am heavily indigenous. Were my ancestors there during Indus Valley Civilization, or did they migrate later and take local wives? I read that the shorthand for R-PF7510/R-F813 is R2A3? So that would mean the paternal line was in India from before Indus Valley right, since I'm seeing R2A3 entered India 25000 years ago? Just very confused the more I read into this stuff...

parasar
10-23-2014, 01:51 AM
Hello all, I'm a new member on here. I joined Biodiversity forum originally in order to discuss my results, but I don't think there are a lot of people that are very knowledgeable on South Asian genetics (at least not active anymore). I am unfortunately still not that well-informed and the whole subject seems like such a political football that I don't know which source to trust. So this is my result.

2777

So to reiterate the attachment, these are my results:
Y-DNA: R-PF7510 (when I transferred to FTDNA, they said R-F813. Are Geno and FTDNA disagreeing or are they same terms?)
MTDNA: M52'58 (same on FTDNA)
Autosomal breakdown:
55% Southwest Asian
25% Southeast Asian
11% Mediterranean
6% Northern European
2% Northeast Asian

...

F813 would be your terminal SNP, so on this FTDNA appears to be correct. I would agree with NatGeo that the so called SW Asian is the oldest South Asian (Y-GHJIKxP331) component.
Your R-F813 likely came from Inner Asia, but as there is R-M479, P(xM45, xM242) and K-M526 in South Asia so there is also a potential of a very ancient South Asian origin for your Y line.
Both your Y(P-P295) and mtDNA lines have a Filipino connection.

redifflal
10-24-2014, 12:10 PM
F813 would be your terminal SNP, so on this FTDNA appears to be correct. I would agree with NatGeo that the so called SW Asian is the oldest South Asian (Y-GHJIKxP331) component.
Your R-F813 likely came from Inner Asia, but as there is R-M479, P(xM45, xM242) and K-M526 in South Asia so there is also a potential of a very ancient South Asian origin for your Y line.
Both your Y(P-P295) and mtDNA lines have a Filipino connection.

Thanks Parasar for your detailed response. Is the Filipino connection for the Y line a remote prehistoric one like saying we are all descended from Y-chromosome Adam in Africa, or is it more in a historical context from Austro-Asiatic farmers moving westwards into the subcontinent? From my reading of R2a's (R-M124), they came from a Central-Asian originated R haplogroup 12000 years ago inside the subcontinent. R's ancestors P and its ancestor K did originate in Southeast Asia. For my sake, "ancient South Asian origin for Y" would be anything beyond 8000BC. I don't know if there is a way to tell definitely with these tests if my ancestors were involved with the beginning of civilization in South Asia, or if they joined in once it was already developing/developed.

Also, how do these autosomal components play out in terms of ANI and ASI? Apparently the two groups had a big mixing event 3500 years ago? Is ASI primarily SW-Asian? I would assume ANI would also have a large SW-Asian proportion themselves as well. I didn't exactly understand what that study proved/showed.

bored
11-17-2014, 10:58 PM
Do you have your raw data? If so, you should upload it to GEDmatch and try out the plethora of calculators that are available there.

redifflal
11-17-2014, 11:10 PM
Do you have your raw data? If so, you should upload it to GEDmatch and try out the plethora of calculators that are available there.

I don't know which raw data GEDMatch will take. I have the .csv file from Geno, it's not really working out that well. I transferred the data to FTDNA, but I can't get the raw data from FTDNA. Has anyone tried using the raw data from Geno for GEDMatch?

ArmandoR1b
11-17-2014, 11:11 PM
Do you have your raw data? If so, you should upload it to GEDmatch and try out the plethora of calculators that are available there.

You can't upload Geno 2.0 raw data to Gedmatch. It's probably because they didn't use enough SNPs. The person would have to purchase a Family Finder test from FTDNA after a free transfer to Geno 2.0 for a raw file that can be uploaded to Gedmatch. The full price is charged for the Family Finder test but they use the Geno 2.0 sample that is at the lab that was sent in for the Geno 2.0 test. Then once they get the Family Finder results they would be able to upload to Gedmatch.

redifflal
11-17-2014, 11:19 PM
You can't upload Geno 2.0 raw data to Gedmatch. It's probably because they didn't use enough SNPs. The person would have to purchase a Family Finder test from FTDNA after a free transfer to Geno 2.0 for a raw file that can be uploaded to Gedmatch. The full price is charged for the Family Finder test but they use the Geno 2.0 sample that is at the lab that was sent in for the Geno 2.0 test. Then once they get the Family Finder results they would be able to upload to Gedmatch.

Ah go figure. I'm not paying anymore at this point behind this. I'm from a pretty insulated part of the subcontinent. I'm not going to fall out of the sky to discover that I'm related to ethnic groups around me (Bihari Brahmins, Orissa tribals, etc). Geno gave me the answers I was looking for in terms of deep ancestry.

bored
11-18-2014, 05:44 AM
Ah go figure. I'm not paying anymore at this point behind this. I'm from a pretty insulated part of the subcontinent. I'm not going to fall out of the sky to discover that I'm related to ethnic groups around me (Bihari Brahmins, Orissa tribals, etc). Geno gave me the answers I was looking for in terms of deep ancestry.

Yep, if I had a lot of disposable income I would go for additional tests but I'm satisfied with the one I did (23andme).

Regarding your Geno 2.0 Results, the Southeast Asian component is capturing most of your ASI. I've heard that Geno 2.0's Southeast Asian approximates ASI rather well. I guess you would score ~50 % on Harappa's South Indian component because roughly half of it is ASI.
The SW Asian is capturing most of your West Eurasian composite. IMO it's got a lot of ANE hidden in it and the rest is South Asia specific EEF ancestry (Gedrosia + SW Asian). Northern European component is mainly ANE as well. The rest of your EEF goes into Mediterranean.

redifflal
11-18-2014, 07:02 PM
Yep, if I had a lot of disposable income I would go for additional tests but I'm satisfied with the one I did (23andme).

Regarding your Geno 2.0 Results, the Southeast Asian component is capturing most of your ASI. I've heard that Geno 2.0's Southeast Asian approximates ASI rather well. I guess you would score ~50 % on Harappa's South Indian component because roughly half of it is ASI.
The SW Asian is capturing most of your West Eurasian composite. IMO it's got a lot of ANE hidden in it and the rest is South Asia specific EEF ancestry (Gedrosia + SW Asian). Northern European component is mainly ANE as well. The rest of your EEF goes into Mediterranean.

I have heard this as well. Yet Geno says the SE-Asian is the Austro-Asiatic rice-farmers, while the SW-Asian is the remnant from the first OOA wave that populated the entire subcontinent. I guess SW Asian then consists of components that would later feed into both ASI and ANI, and SE-Asian or Austro-Asiatics reinforced that ASI somewhat. And the Mediterranean comes from the Neolithic farmers, and the Northern Euro was picked up by Indo-Europeans.

It will be interesting for me to see what my wife's results show. She's Punjabi Khatri with both her mom and her dad's families having made the move during Partition from close to Rawalpindi and Peshawar areas respectively. I'm guessing her SW-Asian is about the same or slightly lower, SE-Asian is probably a lot lower, while Med/North Euro and Northeast Asian in particular are much higher. I keep teasing her about her Chinese looking eyes, we'll see if it shows up LOL.

parasar
11-18-2014, 10:51 PM
I have heard this as well. Yet Geno says the SE-Asian is the Austro-Asiatic rice-farmers, while the SW-Asian is the remnant from the first OOA wave that populated the entire subcontinent. I guess SW Asian then consists of components that would later feed into both ASI and ANI, and SE-Asian or Austro-Asiatics reinforced that ASI somewhat. And the Mediterranean comes from the Neolithic farmers, and the Northern Euro was picked up by Indo-Europeans.

It will be interesting for me to see what my wife's results show. She's Punjabi Khatri with both her mom and her dad's families having made the move during Partition from close to Rawalpindi and Peshawar areas respectively. I'm guessing her SW-Asian is about the same or slightly lower, SE-Asian is probably a lot lower, while Med/North Euro and Northeast Asian in particular are much higher. I keep teasing her about her Chinese looking eyes, we'll see if it shows up LOL.

I would agree except for the Northeast Asian part as I find Nat Geo's 26% NE Asian overlap with Northern Indians difficult to accept. This has to be an error or a very skewed sample set.
https://genographic.nationalgeographic.com/wp-content/uploads/2012/12/populations_Northern-Indian_575.png

redifflal
11-18-2014, 11:04 PM
I would agree except for the Northeast Asian part as I find Nat Geo's 26% NE Asian overlap with Northern Indians difficult to accept. This has to be an error or a very skewed sample set.
https://genographic.nationalgeographic.com/wp-content/uploads/2012/12/populations_Northern-Indian_575.png

Thanks. I wish there was a way to ask National Geographic who or where they sampled in particular for North Indians. In fact, all 4 of their groups should be in question. I hope that they update their database now that they are going to India. I think they should get rid of these 4 regions of India and have really small isolated groups like Sri Lanka Vedda, Jharkhand Santhal, Assam Bodo, Pakistan Kalash, Kashmiri Pandit, Bombay Parsi, etc. Their North Indian reference set does play a spoiler in the general trend from say South Indians to Iranians.

redifflal
02-08-2017, 05:49 PM
Cross-posting Khanabdoshi's work with my Geno 2.0 data here for reference:


OK, so after a bit of work I think I was able to convert the Geno 2.0 file to a suitable FTDNA format. The caveat is that Geno 2.0 files have no build information and thus there are no "positions" associated with the converted file. The file is much tinier than usual raw data files. However, after comparing your results to Reza's family, I feel we can use this file for most calculators.


MDLP K11



0.06% African
1.29% Amerindian
61.53% ASI
0.26% Basal
3.07% Iran-Mesolithic
1.61% Neolithic
0.12% Oceanic
24.13% EHG
3.50% SEA
0.87% Siberian
3.56% WHG



MDLP K16



1.29% Amerindian
0.00% Ancestor
2.10% Steppe
63.78% Indian
0.00% Arctic
1.48% Australian
11.81% Caucasian
0.80% EastAfrican
3.22% NorthEastEuropean
0.00% NearEast
1.55% Neolithic
0.01% NorthAfrican
2.62% Oceanic
2.22% Siberian
9.09% SouthEastAsian
0.03% Subsaharian





MDLP K16 - Comparison w/ Reza's Family





Member
Amerindian
Ancestor
Steppe
Indian
Arctic
Australian
Caucasian
East.African
NE.European
Near.East
Neolithic
North.African
Oceanic
Siberian
SE.Asian
Subsaharan


Mother
0.00%
0.00%
4.45%
54.79%
2.15%
3.01%
11.18%
0.95%
0.41%
0.29%
1.07%
0.00%
1.48%
3.49%
16.73%
0.00%


Reza
0.04%
0.00%
3.88%
55.20%
1.70%
2.50%
8.69%
0.82%
2.12%
0.05%
0.75%
0.00%
0.96%
4.65%
18.63%
0.00%


Wife
0.53%
0.00%
2.88%
58.12%
0.00%
2.27%
8.64%
0.12%
2.53%
0.22%
0.66%
0.23%
1.53%
4.52%
17.95%
0.00%


Father
0.95%
0.00%
3.37%
59.08%
1.42%
2.84%
6.90%
0.57%
0.55%
0.00%
1.69%
1.00%
1.08%
3.58%
16.96%
0.00%


Tanzil
0.35%
0.00%
2.49%
55.87%
0.01%
1.63%
11.35%
0.26%
1.69%
0.00%
0.11%
0.75%
1.95%
3.81%
19.73%
0.00%


Tanzil Uncle
0.43%
0.21%
2.05%
57.63%
0.01%
2.20%
5.90%
0.00%
1.35%
0.00%
1.57%
0.52%
2.64%
4.26%
20.81%
0.42%


Bengali AVG
0.32%
0.56%
2.73%
62.67%
1.23%
2.47%
10.60%
0.17%
0.77%
0.57%
0.16%
0.49%
1.44%
1.99%
12.85%
0.01%


Bangladeshi AVG
0.52%
0.23%
0.27%
69.92%
0.66%
2.63%
0.45%
0.86%
0.29%
0.15%
3.17%
1.41%
1.10%
2.14%
15.96%
0.23%


Redifflal

1.29%
0.00%
2.10%
63.78%
0.00%
1.48%
11.81%
0.80%
3.22%
0.00%
1.55%
0.01%
2.62%
2.22%
9.09%
0.03%





MDLP K16 Oracle



Least-squares method.

Using 1 population approximation:
1 Dharkars @ 3.426241
2 Muslim @ 3.639856
3 Thakur @ 4.492173
4 Tharus @ 4.533473
5 Velamas @ 4.54005
6 Gupta @ 4.594798
7 Punjab @ 5.147086
8 Srivastava @ 5.150588
9 Naidu @ 5.342084
10 GujaratiB_GIH @ 5.419903
11 Lodi @ 5.525417
12 Kurmi @ 5.541871
13 Tamil_Nadu_Scheduled_Caste @ 5.590436
14 Balija @ 5.674496
15 Bengali @ 5.687889
16 Hallaki @ 5.735772
17 Velama @ 5.853666
18 Lambadi @ 5.858575
19 Kanjars @ 6.020598
20 Marwadi @ 6.180804
621 iterations.

Using 2 populations approximation:
1 Kalash+Malayan @ 2.720953
2 GujaratiB_GIH+Hallaki @ 2.81091
3 Kalash+Pulliyar @ 2.876653
4 GujaratiB_GIH+Naidu @ 2.970568
5 GujaratiB_GIH+Punjab @ 3.063584
6 Bengali+GujaratiB_GIH @ 3.091833
7 Punjab+Velamas @ 3.096411
8 Dusadh+GujaratiA_GIH @ 3.118992
9 Marwadi+Punjab @ 3.158493
10 GujaratiA_GIH+Piramalai_Kallars @ 3.212441
11 GujaratiB_GIH+Muslim @ 3.219449
12 Kalash+Paniya @ 3.224796
13 Brahmins_from_Tamil_Nadu+Dusadh @ 3.230273
14 GujaratiB_GIH+Lambadi @ 3.251686
15 GujaratiB_GIH+Tamil_Nadu_Scheduled_Caste @ 3.274342
16 Kalash+Nihali @ 3.29708
17 Balija+GujaratiB_GIH @ 3.326158
18 Dharkars+Muslim @ 3.334831
19 Brahmin_Tamil+Piramalai_Kallars @ 3.33922
20 Brahmins_from_Tamil_Nadu+Kol @ 3.341376
193131 iterations.

Using 3 populations approximation:
1 50% Chenchus +25% GujaratiB_GIH +25% Kalash @ 2.117097
2 50% Muslim +25% Bengali_Bangladesh_BEB +25% Kalash @ 2.119071
3 50% Piramalai_Kallars +25% Kalash +25% Punjab @ 2.145542
4 50% Tharu +25% GujaratiC_GIH +25% Kalash @ 2.179571
5 50% Dusadh +25% Kalash +25% Punjab @ 2.200079
6 50% Muslim +25% Kalash +25% Mala @ 2.229576
7 50% Muslim +25% Kalash +25% Madiga @ 2.242902
8 50% Piramalai_Kallars +25% Kalash +25% Tharu @ 2.249483
9 50% Brahmins_from_Tamil_Nadu +25% Punjab +25% Punjabi_Lahore_PJL @ 2.264616
10 50% Tamil_Nadu_Scheduled_Caste +25% GujaratiA_GIH +25% Punjab @ 2.289369
11 50% Muslim +25% Bhil +25% Kalash @ 2.29469
12 50% Kamsali +25% Kalash +25% Punjab @ 2.314997
13 50% Bhil +25% Brahmins_from_Tamil_Nadu +25% Kalash @ 2.339856
14 50% Kol +25% Kalash +25% Punjab @ 2.34407
15 50% Mala +25% Kalash +25% Meena @ 2.350396
16 50% Muslim +25% Chamar +25% Kalash @ 2.363893
17 50% Muslim +25% Kalash +25% North_Kannadi @ 2.366971
18 50% Piramalai_Kallars +25% GujaratiA_GIH +25% Punjab @ 2.370687
19 50% Dharkars +25% Kalash +25% Mala @ 2.372828
20 50% Tharu +25% GujaratiD_GIH +25% Kalash @ 2.378508
34344076 iterations.

Using 4 populations approximation:
1 GujaratiB_GIH+Kalash+Nihali+Tamil_Nadu_Scheduled_C aste @ 1.83068
2 Dhaka-mixed-popul+GujaratiC_GIH+Kalash+Naidu @ 1.839604
3 Chenchu+GujaratiB_GIH+Kalash+Piramalai_Kallars @ 1.854622
4 Dhaka-mixed-popul+GujaratiC_GIH+Hallaki+Kalash @ 1.861935
5 GujaratiB_GIH+Kalash+Piramalai_Kallars+Satnami @ 1.889785
6 Kalash+Kol+Naidu+Punjab @ 1.89478
7 Bhil+Kalash+Kurmi+Punjab @ 1.89651
8 Kalash+Mala+Muslim+Punjab @ 1.906662
9 GujaratiB_GIH+Kalash+Naidu+Nihali @ 1.909249
10 Kalash+Madiga+Muslim+Punjab @ 1.909775
11 Brahmins_from_Tamil_Nadu+GujaratiC_GIH+Kalash+Niha li @ 1.91471
12 Bhil+Kalash+Naidu+Punjab @ 1.916802
13 GujaratiB_GIH+Kalash+Nihali+Piramalai_Kallars @ 1.921032
14 Kalash+Meena+Nihali+Punjabi_Lahore_PJL @ 1.926114
15 Dhaka-mixed-popul+GujaratiC_GIH+Kalash+Piramalai_Kallars @ 1.928551
16 Bengali_Bangladesh_BEB+Bhil+Kalash+Meena @ 1.92995
17 GujaratiC_GIH+Kalash+Meghawal+Nihali @ 1.933765
18 Dhaka-mixed-popul+GujaratiC_GIH+Kalash+Tamil_Nadu_Scheduled_Ca ste @ 1.933982
19 Chenchu+GujaratiB_GIH+Kalash+Tamil_Nadu_Scheduled_ Caste @ 1.934079
20 Dhaka-mixed-popul+GujaratiC_GIH+Gupta+Kalash @ 1.937428
21 Gond+GujaratiD_GIH+Kalash+Meghawal @ 1.940166
22 GujaratiD_GIH+Kalash+Kshatriya+Nihali @ 1.941351
23 Kalash+Kurmi+Madiga+Punjab @ 1.942504
24 Kalash+Kurmi+Mala+Punjab @ 1.944691
25 Chenchu+GujaratiB_GIH+Kalash+Naidu @ 1.946981
26 Balija+Dhaka-mixed-popul+GujaratiC_GIH+Kalash @ 1.947193
27 Kalash+Kol+Piramalai_Kallars+Punjab @ 1.947278
28 Gond+GujaratiC_GIH+Kalash+Muslim @ 1.953233
29 GujaratiB_GIH+Kalash+Malayan+Naidu @ 1.956913
30 Dhaka-mixed-popul+GujaratiC_GIH+Kalash+Punjab @ 1.95748
31 GujaratiB_GIH+Kalash+Malayan+Tamil_Nadu_Scheduled_ Caste @ 1.969648
32 GujaratiD_GIH+Kalash+Meena+Nihali @ 1.972112
33 Kalash+Mala+Naidu+Punjab @ 1.98006
34 GujaratiB_GIH+Kalash+Nihali+Velamas @ 1.981447
35 Bengali_Bangladesh_BEB+Kalash+Mala+Meena @ 1.982105
36 Chenchus+Kalash+Piramalai_Kallars+Punjab @ 1.989051
37 Dhaka-mixed-popul+GujaratiC_GIH+Kalash+Lodi @ 1.992175
38 Dhaka-mixed-popul+Kalash+Punjabi_Lahore_PJL+Velamas @ 1.992448
39 GujaratiB_GIH+Kalash+Naidu+Pulliyar @ 1.992657
40 GujaratiD_GIH+Kalash+Meghawal+Satnami @ 1.993118
376676379 iterations.


Gaussian method.
Noise dispersion set to 0.31652

Using 1 population approximation:
1 Punjab @ 4.355287
2 GujaratiB_GIH @ 4.448415
3 Muslim @ 4.582623
4 Gupta @ 4.938563
5 GujaratiC_GIH @ 5.136478
6 Dharkars @ 5.145598
7 Tharus @ 5.418768
8 Srivastava @ 5.528044
9 Thakur @ 5.636148
10 Dusadh @ 5.701683
11 Meghawal @ 5.858672
12 Orissa @ 5.913078
13 Kshatriya @ 6.026218
14 Brahmin_Tamil @ 6.047493
15 Brahmins_from_Uttar_Pradesh @ 6.101713
16 Lambadi @ 6.119246
17 Vaish @ 6.201197
18 Hallaki @ 6.311745
19 Tharu @ 6.329971
20 Lodi @ 6.33546
621 iterations.

Using 2 populations approximation:
1 GujaratiB_GIH+Muslim @ 4.111896
2 GujaratiB_GIH+Punjab @ 4.132676
3 Muslim+Punjab @ 4.159195
4 GujaratiC_GIH+Punjab @ 4.180147
5 GujaratiB_GIH+Gupta @ 4.272827
6 GujaratiB_GIH+GujaratiC_GIH @ 4.277372
7 GujaratiC_GIH+Muslim @ 4.29146
8 Dusadh+GujaratiB_GIH @ 4.330345
9 Punjab+Punjab @ 4.355287
10 GujaratiB_GIH+Lambadi @ 4.359061
11 GujaratiB_GIH+GujaratiD_GIH @ 4.368625
12 Dhaka-mixed-popul+GujaratiB_GIH @ 4.396527
13 GujaratiD_GIH+Kshatriya @ 4.425613
14 GujaratiB_GIH+Kurmi @ 4.441934
15 Gupta+Punjab @ 4.445691
16 Lambadi+Punjab @ 4.448176
17 GujaratiB_GIH+GujaratiB_GIH @ 4.448415
18 GujaratiB_GIH+Tamil_Nadu_Scheduled_Caste @ 4.468698
19 GujaratiD_GIH+Meena @ 4.471896
20 Chenchu+Kalash @ 4.474698
193131 iterations.

Using 3 populations approximation:
1 50% GujaratiC_GIH +25% Dhaka-mixed-popul +25% Kalash @ 3.575345
2 50% GujaratiD_GIH +25% Dhaka-mixed-popul +25% Kalash @ 3.722945
3 50% GujaratiD_GIH +25% Brahmins_from_Uttaranchal +25% Kalash @ 3.900001
4 50% GujaratiB_GIH +25% Dhaka-mixed-popul +25% GujaratiC_GIH @ 3.931138
5 50% Dhaka-mixed-popul +25% GujaratiC_GIH +25% Kalash @ 3.935206
6 50% GujaratiB_GIH +25% Dhaka-mixed-popul +25% GujaratiD_GIH @ 3.95393
7 50% Muslim +25% GujaratiD_GIH +25% Kalash @ 3.971567
8 50% GujaratiC_GIH +25% Brahmins_from_Uttaranchal +25% Kalash @ 3.9725
9 50% Muslim +25% GujaratiC_GIH +25% Kalash @ 3.986246
10 50% GujaratiC_GIH +25% Kalash +25% Muslim @ 4.000585
11 50% GujaratiB_GIH +25% Dhaka-mixed-popul +25% GujaratiB_GIH @ 4.003559
12 50% Dhaka-mixed-popul +25% GujaratiD_GIH +25% Kalash @ 4.01369
13 50% GujaratiC_GIH +25% Chenchu +25% Kalash @ 4.019394
14 50% GujaratiD_GIH +25% Kalash +25% Muslim @ 4.02879
15 50% Muslim +25% GujaratiC_GIH +25% Punjab @ 4.029079
16 50% GujaratiB_GIH +25% GujaratiD_GIH +25% Muslim @ 4.036567
17 50% GujaratiB_GIH +25% Muslim +25% Punjab @ 4.051037
18 50% Muslim +25% GujaratiB_GIH +25% GujaratiC_GIH @ 4.052085
19 50% GujaratiC_GIH +25% Dhaka-mixed-popul +25% Meena @ 4.053516
20 50% GujaratiB_GIH +25% GujaratiC_GIH +25% Muslim @ 4.054348
116504567 iterations.

Using 4 populations approximation:
1 Dhaka-mixed-popul+GujaratiC_GIH+GujaratiC_GIH+Kalash @ 3.575345
2 Dhaka-mixed-popul+GujaratiC_GIH+GujaratiD_GIH+Kalash @ 3.619246
3 Dhaka-mixed-popul+GujaratiD_GIH+GujaratiD_GIH+Kalash @ 3.722945
4 Dhaka-mixed-popul+GujaratiB_GIH+GujaratiD_GIH+Kalash @ 3.7501
5 Dhaka-mixed-popul+GujaratiC_GIH+Kalash+Punjab @ 3.771123
6 Dhaka-mixed-popul+GujaratiB_GIH+GujaratiC_GIH+Kalash @ 3.773148
7 Dhaka-mixed-popul+GujaratiD_GIH+Kalash+Punjab @ 3.780138
8 Dhaka-mixed-popul+GujaratiC_GIH+Kalash+Kurmi @ 3.799797
9 Dhaka-mixed-popul+GujaratiC_GIH+Kalash+Muslim @ 3.809436
10 Dhaka-mixed-popul+GujaratiC_GIH+Gupta+Kalash @ 3.813307
11 Dhaka-mixed-popul+GujaratiD_GIH+Kalash+Kurmi @ 3.830393
12 Dhaka-mixed-popul+GujaratiD_GIH+Kalash+Muslim @ 3.845811
13 Dhaka-mixed-popul+GujaratiD_GIH+Gupta+Kalash @ 3.854873
14 Brahmins_from_Uttaranchal+GujaratiD_GIH+GujaratiD_ GIH+Kalash @ 3.900001
15 Dhaka-mixed-popul+Dusadh+GujaratiC_GIH+Kalash @ 3.913268
16 Dhaka-mixed-popul+GujaratiC_GIH+Kalash+Tamil_Nadu_Scheduled_Ca ste @ 3.915833
17 Brahmins_from_Uttaranchal+GujaratiC_GIH+GujaratiD_ GIH+Kalash @ 3.917948
18 Dhaka-mixed-popul+GujaratiB_GIH+GujaratiB_GIH+GujaratiC_GIH @ 3.931138
19 Dhaka-mixed-popul+GujaratiC_GIH+Kalash+Punjabi_Lahore_PJL @ 3.933143
20 Dhaka-mixed-popul+Dhaka-mixed-popul+GujaratiC_GIH+Kalash @ 3.935206
21 GujaratiD_GIH+Kalash+Muslim+Punjab @ 3.936254
22 Dhaka-mixed-popul+GujaratiB_GIH+GujaratiB_GIH+GujaratiD_GIH @ 3.95393
23 GujaratiB_GIH+GujaratiC_GIH+Muslim+Punjab @ 3.967532
24 GujaratiC_GIH+Kalash+Muslim+Punjab @ 3.970207
25 GujaratiD_GIH+Kalash+Muslim+Muslim @ 3.971567
26 Brahmins_from_Uttaranchal+GujaratiC_GIH+GujaratiC_ GIH+Kalash @ 3.9725
27 Dhaka-mixed-popul+GujaratiC_GIH+Kalash+Piramalai_Kallars @ 3.980494
28 GujaratiB_GIH+GujaratiD_GIH+Muslim+Punjab @ 3.982482
29 Dhaka-mixed-popul+GujaratiC_GIH+Kalash+Marwadi @ 3.983161
30 GujaratiC_GIH+GujaratiD_GIH+Kalash+Muslim @ 3.985011
31 GujaratiD_GIH+Kalash+Kurmi+Muslim @ 3.985281
32 GujaratiC_GIH+Kalash+Muslim+Muslim @ 3.986246
33 Dhaka-mixed-popul+Dusadh+GujaratiD_GIH+Kalash @ 3.988789
34 Dhaka-mixed-popul+GujaratiC_GIH+Kalash+Lambadi @ 3.992927
35 GujaratiC_GIH+Kalash+Kurmi+Muslim @ 3.994867
36 Dhaka-mixed-popul+GujaratiD_GIH+Kalash+Punjabi_Lahore_PJL @ 3.994997
37 GujaratiC_GIH+GujaratiC_GIH+Kalash+Muslim @ 4.000585
38 Dhaka-mixed-popul+GujaratiB_GIH+GujaratiB_GIH+GujaratiB_GIH @ 4.003559
39 Dhaka-mixed-popul+Dhaka-mixed-popul+GujaratiD_GIH+Kalash @ 4.01369
40 Dhaka-mixed-popul+GujaratiB_GIH+GujaratiD_GIH+Meena @ 4.016694
1539319710 iterations.





Turkic K9 - Seems off here, but I believe this was an early iteration of the calculator. I ran it because I had it readily available.





Member
SE EUROPEAN
W ASIAN
SSA
NE EUROPEAN
INDIAN
MONGOLIAN
PAPUAN
NE ASIAN
TURKIC


Reza
0.45%
0.72%
0.00%
0.88%
73.15%
8.15%
0.77%
0.07%
15.79%


Lionheart Mother (AncestryDNA)
0.04%
9.38%
0.07%
9.08%
67.77%
3.76%
1.66%
0.00%
8.25%


Redifflal

1.80%
10.51%
0.02%
9.60%
66.75%
3.75%
1.40%
0.00%
6.17%




Iran Neolithic K6





Member
ASE
E ASIAN
IRAN N
NATUFIAN
WHG
SSA


Bengali
24.10%
20.00%
51.50%
0.30%
3.90%
0.10%


Bangladesh; Bengali - Reza
20.43%
24.21%
50.72%
0.01%
4.63%
0.00%


redifflal

24.13%
14.38%
51.07%
2.33%
8.08%
0.02%




puntDNAL K12





Member
EHG-STEPPE
OCEANIAN
E_EURASIAN
IRAN_N
SIBERIAN
SUB-SAHARAN
AFRICAN_HG
S_EURASIAN
WESTERN_HG
NATUFIAN_HG
AMERINDIAN
ANATOLIAN_N


Bangladesh; Bengali - Reza
6.22%
0.48%
8.89%
18.30%
3.81%
0.00%
0.84%
52.87%
3.67%
3.00%
1.84%
0.11%


Bengali
7.13%
0.89%
7.45%
19.39%
3.01%
0.11%
0.09%
54.29%
2.89%
2.77%
1.15%
0.83%


redifflal

11.42%
2.30%
1.35%
19.14%
2.47%
0.38%
0.00%
55.99%
3.28%
0.01%
0.00%
3.65%





We will have to try on some other calculators to see if the results make sense. So far it doesn't seem too bad. I've uploaded the file to Gedmatch using the Generic method. I don't think it will work -- but you never know. I think we can at least use the file for DIY calculators.


The Gedmatch upload won't work. I'll need a DIY version of Harrapa to run it. Have a link?

EDIT: Found it.

51.81% S-Indian
33.59% Baloch
2.77% Caucasian
7.91% NE-Euro
0.44% SE-Asian
1.23% Siberian
1.08% NE-Asian
0.01% Papuan
0.51% American
0.10% Beringian
0.00% Mediterranean
0.54% SW-Asian
0.00% San
0.00% E-African
0.00% Pygmy
0.00% W-African

MonkeyDLuffy
02-09-2017, 01:31 AM
Cross-posting Khanabdoshi's work with my Geno 2.0 data here for reference:

I actually expected high NE or SE asian from your results but seems like they're more similar to a central Indian or someone from Maharashtra and surrounding area.

redifflal
02-13-2017, 02:48 PM
I actually expected high NE or SE asian from your results but seems like they're more similar to a central Indian or someone from Maharashtra and surrounding area.

If you see the original Geno auto breakdown, you'd see the NE and SE Asian scores are about half of the Bengali/Eastern-Indian averages. I'll get folks on my mom's side tested, I'm sure their scores will be more along the lines as expected from Bengalis.