PCA G25_scaled - Africans only (Users & Ancients/Modern Avgs)

[Ramses]

I already had them in K13 estimates , its not very accurate but it exposes whether they had More west asian or Horn african ancestry.
Model that exposes West asian ancestry


Model that exposes Mota ancestry(Approximate)


The Beniamer have some horn african ancestry+arab, other sudanese arabs look more arab+nilotic mix.

[ThaYamamoto]

Angoliga do you reckon you can add me to the PCA now - using mixed mode oracles on my coordinates and the datasheets surprisingly got me results in keeping with where I'd plot on the PCA explaining why I plot ahead of Egyptians but not ahead of IBM+SSA harboring folks.

Oracle Calculator by www.dnagenics.com
v1.9  04/09/2020

Finished reading population data. 577 populations found.
25 components mode.

B distance calculation method.

--------------------------------


Mixed Mode:
1 56.25% Brahmin_Uttar_Pradesh + 43.75% Kalash @ 0.779
2 56.25% Dharkar + 43.75% Kalash @ 0.866
3 81.25% Brahmin_Uttar_Pradesh + 18.75% Ndau @ 0.884
4 56.25% Brahmin_Uttar_Pradesh + 43.75% Makrani @ 0.911
5 56.25% Brahmin_Uttar_Pradesh + 43.75% Brahui @ 0.911
6 68.75% Brahmin_Uttar_Pradesh + 31.25% Iraqi @ 0.916
7 56.25% Balochi + 43.75% Uttar_Pradesh @ 0.927
8 56.25% Makrani + 43.75% Uttar_Pradesh @ 0.936
9 56.25% Brahui + 43.75% Uttar_Pradesh @ 0.936
10 81.25% Brahmin_Uttar_Pradesh + 18.75% Luo @ 0.939

i was actually hella surprised the algorithm was able to pick this up. bear in mind the figure ~18% is an exact match for my max AncestryDNA range and SAPDA results which i can attach later. this might be the most parsimonious use of the algorithm to explain my position on the intra-african pca. removing makrani, kalash and brahmin got me even closer (as im far closer to the kamboj group than to brahmins)

Oracle Calculator by www.dnagenics.com
v1.9  04/09/2020

Finished reading population data. 574 populations found.
25 components mode.

B distance calculation method.

--------------------------------


Mixed Mode:
1 81.25% Kamboj + 18.75% Luo @ 1.154
2 56.25% Tajik + 43.75% Uttar_Pradesh @ 1.155
3 68.75% Dharkar + 31.25% Parsi_Pakistan @ 1.155
4 68.75% Dharkar + 31.25% Tajik_Rushan @ 1.157
5 68.75% Balochi + 31.25% Relli @ 1.164
6 56.25% Ror + 43.75% Uttar_Pradesh @ 1.165
7 68.75% Dharkar + 31.25% Iranian_Lor @ 1.168
8 56.25% Pashtun + 43.75% Uttar_Pradesh @ 1.170
9 56.25% Azeri + 43.75% Gupta @ 1.172
10 81.25% Kamboj + 18.75% Ndau @ 1.173

i was only able to achieve this via multiethnic nMonte and mixed mode oracles on the g25. was pleasantly surprised.

[Chad Rohlfsen]

Okay, so I am looking at this really closely here. I think there isn't any Dinka or Mota ancestry in the Early Pastoralists. They are almost full Basal Eurasian, or North African, if you will. I really think that there is actual West African ancestry in the Iberomaurusians. They are much closer to Sub-Saharans than anyone else and this doesn't translate into Natufians. So, there obviously cant be any IBM>Natufian flow. It is in the other direction, with some West African and maybe Nilotic ancestry in Iberomaurusians.

I have a graph here below, but I see something in it that I can use to create something much better.

Pastoralist.png

I think this may be more important than the stuff with South Asians and the Xiongnu. I am still going to complete both of those, as well as another I am doing on Indus Periphery ancestry being much more prevalent than what was thought. Mesopotamian ancestry as well, all over.

I also have plenty of D-stats and some qpAdm to show what I am thinking here. Let's go ahead and open up a conversation here. Give me some feedback on something you want me to look at.

[TuaMan]

Okay, so I am looking at this really closely here. I think there isn't any Dinka or Mota ancestry in the Early Pastoralists. They are almost full Basal Eurasian, or North African, if you will. I really think that there is actual West African ancestry in the Iberomaurusians. They are much closer to Sub-Saharans than anyone else and this doesn't translate into Natufians. So, there obviously cant be any IBM>Natufian flow. It is in the other direction, with some West African and maybe Nilotic ancestry in Iberomaurusians.

I have a graph here below, but I see something in it that I can use to create something much better.

Attachment 41552

I think this may be more important than the stuff with South Asians and the Xiongnu. I am still going to complete both of those, as well as another I am doing on Indus Periphery ancestry being much more prevalent than what was thought. Mesopotamian ancestry as well, all over.

I also have plenty of D-stats and some qpAdm to show what I am thinking here. Let's go ahead and open up a conversation here. Give me some feedback on something you want me to look at.

Your attachment doesn't seem to be working, at least for me.

I would need to double check the original paper but I'm pretty sure the early East African pastoralists also had some unquestionably SSA uniparentals (namely different varieties of L mtDNA) so they're unlikely to be purely BE or North African migrants.

[Chad Rohlfsen]

You can see below that there is nothing even closely resembling a feasible model from these populations. Even if one or more was not needed, there should still be a passing or near passing model somewhere in the output that tells you which populations are set to .000, or not needed in the model. That is one useful deal about qpAdm. So, there is obviously something amiss here. Not just here, but in the qpGraph and D-stats that suggests there isn't anything deeper in the two early pastoralists that can't just be modeled as Basal Eurasian. I think the Pastoralist individuals are the missing link to make a successful model. I'm going to be testing this out.

left pops:
Hadendowa
Natufian
Levant_N
BedouinB
Dinka
Mota.SG

right pops:
Chimp
South_Africa_2000BP.SG
Shum_Laka.SG
Mende
Nuer
Ust_Ishim
Brazil_LapaDoSanto_9600BP
Iron_Gates_HG
Yana
Tianyuan
SunghirIV
GoyetQ116-1
EHG
Taiwan_Hanben
IBM
Barcin_N
CHG
Ganj_Dareh_N
Jomon
Paleo_Aleut
Boisman_MN
Aeta
Onge

0 Hadendowa 14
1 Natufian 6
2 Levant_N 15
3 BedouinB 2
4 Dinka 2
5 Mota.SG 1
6 Chimp 1
7 South_Africa_2000BP.SG 2
8 Shum_Laka.SG 1
9 Mende 2
10 Nuer 16
11 Ust_Ishim 1
12 Brazil_LapaDoSanto_9600BP 6
13 Iron_Gates_HG 40
14 Yana 2
15 Tianyuan 1
16 SunghirIV 1
17 GoyetQ116-1 1
18 EHG 3
19 Taiwan_Hanben 48
20 IBM 4
21 Barcin_N 25
22 CHG 2
23 Ganj_Dareh_N 8
24 Jomon 6
25 Paleo_Aleut 4
26 Boisman_MN 12
27 Aeta 3
28 Onge 11
jackknife block size: 0.050
snps: 1150636 indivs: 240
number of blocks for block jackknife: 713
## ncols: 1150636
coverage: Hadendowa 565352
coverage: Natufian 514148
coverage: Levant_N 904850
coverage: BedouinB 781454
coverage: Dinka 781455
coverage: Mota.SG 1149598
coverage: Chimp 1102442
coverage: South_Africa_2000BP.SG 1087703
coverage: Shum_Laka.SG 1147190
coverage: Mende 769394
coverage: Nuer 565348
coverage: Ust_Ishim 1147829
coverage: Brazil_LapaDoSanto_9600BP 961887
coverage: Iron_Gates_HG 1141414
coverage: Yana 1149918
coverage: Tianyuan 844120
coverage: SunghirIV 1138519
coverage: GoyetQ116-1 765579
coverage: EHG 1027057
coverage: Taiwan_Hanben 1138853
coverage: IBM 1090734
coverage: Barcin_N 1137966
coverage: CHG 1149558
coverage: Ganj_Dareh_N 1057358
coverage: Jomon 935910
coverage: Paleo_Aleut 960525
coverage: Boisman_MN 1031750
coverage: Aeta 1060714
coverage: Onge 616424
dof (jackknife): 601.806
numsnps used: 44649
codimension 1
f4info:
f4rank: 4 dof: 18 chisq: 88.596 tail: 2.57751226e-11 dofdiff: 20 chisqdiff: -88.596 taildiff: 1
B:
scale 1.000 1.000 1.000 1.000
South_Africa_2000BP.SG -0.072 -0.528 -1.064 -1.544
Shum_Laka.SG -0.021 -0.247 0.008 -0.602
Mende -0.076 0.552 0.166 -0.183
Nuer -0.159 3.394 3.444 2.354
Ust_Ishim 0.962 -0.287 -1.669 0.381
Brazil_LapaDoSanto_9600BP 1.095 -0.621 -0.245 -0.651
Iron_Gates_HG 1.331 -1.083 0.019 0.179
Yana 1.048 -0.115 0.146 0.335
Tianyuan 0.978 0.038 0.171 0.109
SunghirIV 1.125 0.227 -0.623 0.461
GoyetQ116-1 1.169 -0.833 -0.177 0.274
EHG 1.234 0.200 0.221 -0.428
Taiwan_Hanben 1.001 -0.189 -0.700 -0.148
IBM 0.882 -0.258 -1.172 2.846
Barcin_N 1.500 -2.058 1.864 0.924
CHG 1.227 0.770 -0.182 -0.566
Ganj_Dareh_N 1.189 0.801 0.146 -0.514
Jomon 1.036 0.546 0.260 -0.098
Paleo_Aleut 1.044 0.755 0.059 -0.468
Boisman_MN 0.994 -0.753 -0.162 0.218
Aeta 0.931 0.562 0.307 -1.540
Onge 0.942 0.262 -0.166 -0.520
A:
scale 74.109 1530.519 3509.329 1830.186
Natufian 0.884 -1.272 -1.890 1.235
Levant_N 1.018 -1.435 0.909 -0.096
BedouinB 0.969 0.303 -0.024 -1.147
Dinka -1.122 -0.251 0.244 0.132
Mota.SG -0.992 -1.081 -0.737 -1.460


full rank
f4info:
f4rank: 5 dof: 0 chisq: 0.000 tail: 1 dofdiff: 18 chisqdiff: 88.596 taildiff: 2.57751226e-11
B:
scale 1.000 1.000 1.000 1.000 1.000
South_Africa_2000BP.SG -0.081 -1.263 -1.089 -1.075 -0.033
Shum_Laka.SG -0.015 -0.447 -0.344 -0.138 -0.880
Mende -0.073 -0.748 0.135 0.834 -0.827
Nuer -0.141 1.214 -0.520 3.932 1.582
Ust_Ishim 0.958 -0.447 1.742 -0.452 0.328
Brazil_LapaDoSanto_9600BP 1.091 -0.198 -0.473 -0.812 -0.134
Iron_Gates_HG 1.329 0.676 0.538 -0.807 -0.697
Yana 1.052 0.169 0.455 0.151 -0.515
Tianyuan 0.981 -0.250 0.467 0.323 -0.857
SunghirIV 1.123 0.176 0.654 0.057 0.737
GoyetQ116-1 1.173 0.350 0.529 -0.618 -0.364
EHG 1.235 -0.321 -0.659 0.076 0.118
Taiwan_Hanben 1.003 -0.298 0.850 -0.247 -0.263
IBM 0.869 2.566 2.272 -0.118 2.333
Barcin_N 1.493 2.661 0.375 -1.255 -2.497
CHG 1.235 -0.907 -0.400 0.474 0.472
Ganj_Dareh_N 1.197 -0.675 -0.985 0.513 0.789
Jomon 1.031 0.191 -0.834 0.236 1.115
Paleo_Aleut 1.049 -0.483 -0.784 0.406 0.712
Boisman_MN 0.991 0.340 1.048 -0.504 -1.015
Aeta 0.934 -1.270 -2.307 0.132 0.205
Onge 0.944 -0.316 -0.641 -0.081 0.569
A:
scale 75.668 2391.996 3296.374 1376.059 3625.366
Natufian 0.871 0.614 1.954 -1.331 0.627
Levant_N 1.029 0.791 -0.195 -0.932 -1.108
BedouinB 0.999 -1.525 -0.051 0.089 -1.018
Dinka -1.091 -0.536 0.890 0.569 -1.446
Mota.SG -0.997 -1.177 -0.591 -1.424 -0.502


best coefficients: 0.134 -0.010 0.429 0.615 -0.167
Jackknife mean: -0.654835121 0.522973947 0.624016147 0.409157023 0.098688004
std. errors: 0.296 0.344 0.116 0.059 0.077

error covariance (* 1000000)
87783 -98681 19777 4213 -13092
-98681 118415 -30398 -3471 14135
19777 -30398 13508 -67 -2820
4213 -3471 -67 3435 -4110
-13092 14135 -2820 -4110 5887


summ: Hadendowa 5 0.000000 -0.655 0.523 0.624 0.409 0.099 87783 -98681 19777 4213 -13092 118415 -30398 -3471 14135 13508 ...
-67 -2820 3435 -4110 5887

fixed pat wt dof chisq tail prob
00000 0 18 88.596 2.57751e-11 0.134 -0.010 0.429 0.615 -0.167 infeasible
00001 1 19 86.924 1.15783e-10 0.388 -0.356 0.523 0.445 -0.000 infeasible
00010 1 19 92.635 1.12829e-11 14.946 -17.380 4.272 0.411 -1.249 infeasible
00100 1 19 95.068 4.14508e-12 -2.455 2.815 0.000 0.743 -0.103 infeasible
01000 1 19 88.715 5.59918e-11 0.136 0.000 0.416 0.622 -0.174 infeasible
10000 1 19 87.082 1.08606e-10 0.000 0.122 0.422 0.623 -0.167 infeasible
00011 2 20 111.596 1.00419e-14 5.639 -6.866 2.227 -0.000 -0.000 infeasible
00101 2 20 95.774 7.1314e-12 -2.680 3.014 0.000 0.665 -0.000 infeasible
00110 2 20 117.973 6.76043e-16 -44.675 42.158 0.000 0.000 3.517 infeasible
01001 2 20 99.657 1.45084e-12 0.107 -0.000 0.425 0.468 -0.000
01010 2 20 160.780 5.30723e-24 -2.632 0.000 3.205 -0.000 0.427 infeasible
01100 2 20 128.753 6.6766e-18 0.551 0.000 0.000 0.712 -0.263 infeasible
10001 2 20 108.992 2.99775e-14 -0.000 0.048 0.484 0.469 -0.000
10010 2 20 137.226 1.69711e-19 -0.000 -3.270 4.111 -0.000 0.159 infeasible
10100 2 20 101.403 7.05856e-13 -0.000 0.514 0.000 0.711 -0.225 infeasible
11000 2 20 111.776 9.30782e-15 -0.000 0.000 0.554 0.597 -0.151 infeasible
00111 3 21 136.019 7.63863e-19 9.488 -8.488 0.000 -0.000 -0.000 infeasible
01011 3 21 170.485 2.07602e-25 -16.524 0.396 17.312 -0.015 -0.170 infeasible
01101 3 21 141.102 8.47926e-20 0.517 -0.000 0.000 0.483 -0.000
01110 3 21 272.206 0 0.434 0.000 0.000 -0.000 0.566
10011 3 21 204.552 0 0.000 -4.165 5.165 -0.000 -0.000 infeasible
10101 3 21 126.411 4.7024e-17 -0.000 0.487 0.000 0.513 -0.000
10110 3 21 258.265 0 -0.000 0.403 0.000 0.000 0.597
11001 3 21 122.797 2.1857e-16 0.000 -0.000 0.536 0.464 -0.000
11010 3 21 253.633 0 0.000 0.000 0.461 -0.000 0.539
11100 3 21 234.766 0 0.000 -0.000 0.000 -2.744 3.744 infeasible
01111 4 22 1392.578 0 1.000 0.000 0.000 -0.000 -0.000
10111 4 22 2481.224 0 0.000 1.000 0.000 -0.000 -0.000
11011 4 22 1657.061 0 0.000 0.000 1.000 -0.000 -0.000
11101 4 22 2356.303 0 0.000 0.000 0.000 1.000 -0.000
11110 4 22 983.523 0 0.000 0.000 0.000 -0.000 1.000

[TuaMan]

Also, what kind of West African > IBM are you thinking specifically? Gambian, Yoruba, Shum Laka, or you can't tell that granularly?

[Chad Rohlfsen]

Your attachment doesn't seem to be working, at least for me.

I would need to double check the original paper but I'm pretty sure the early East African pastoralists also had some unquestionably SSA uniparentals (namely different varieties of L mtDNA) so they're unlikely to be purely BE or North African migrants.

I fixed the link above. I've checked the uniparentals on there. I don't see anything really that we can say is without a doubt connected to SSA. It was L3 and K1 mtDNA and E2 for the one Y. I don't think any of these can be ruled out as being part of that group. A Basal group should straddle both Eurasian and Sub-Saharan in markers..or the overlap, if you will. I'm sure we can't also say zero flow ever occurred after the split and it is lost in bigger picture.

[Chad Rohlfsen]

Also, what kind of West African > IBM are you thinking specifically? Gambian, Yoruba, Shum Laka, or you can't tell that granularly?

I'm looking at this.

[Mnemonics]

You can see below that there is nothing even closely resembling a feasible model from these populations. Even if one or more was not needed, there should still be a passing or near passing model somewhere in the output that tells you which populations are set to .000, or not needed in the model. That is one useful deal about qpAdm. So, there is obviously something amiss here. Not just here, but in the qpGraph and D-stats that suggests there isn't anything deeper in the two early pastoralists that can't just be modeled as Basal Eurasian. I think the Pastoralist individuals are the missing link to make a successful model. I'm going to be testing this out.

left pops:
Hadendowa
Natufian
Levant_N
BedouinB
Dinka
Mota.SG

right pops:
Chimp
South_Africa_2000BP.SG
Shum_Laka.SG
Mende
Nuer
Ust_Ishim
Brazil_LapaDoSanto_9600BP
Iron_Gates_HG
Yana
Tianyuan
SunghirIV
GoyetQ116-1
EHG
Taiwan_Hanben
IBM
Barcin_N
CHG
Ganj_Dareh_N
Jomon
Paleo_Aleut
Boisman_MN
Aeta
Onge

0 Hadendowa 14
1 Natufian 6
2 Levant_N 15
3 BedouinB 2
4 Dinka 2
5 Mota.SG 1
6 Chimp 1
7 South_Africa_2000BP.SG 2
8 Shum_Laka.SG 1
9 Mende 2
10 Nuer 16
11 Ust_Ishim 1
12 Brazil_LapaDoSanto_9600BP 6
13 Iron_Gates_HG 40
14 Yana 2
15 Tianyuan 1
16 SunghirIV 1
17 GoyetQ116-1 1
18 EHG 3
19 Taiwan_Hanben 48
20 IBM 4
21 Barcin_N 25
22 CHG 2
23 Ganj_Dareh_N 8
24 Jomon 6
25 Paleo_Aleut 4
26 Boisman_MN 12
27 Aeta 3
28 Onge 11
jackknife block size: 0.050
snps: 1150636 indivs: 240
number of blocks for block jackknife: 713
## ncols: 1150636
coverage: Hadendowa 565352
coverage: Natufian 514148
coverage: Levant_N 904850
coverage: BedouinB 781454
coverage: Dinka 781455
coverage: Mota.SG 1149598
coverage: Chimp 1102442
coverage: South_Africa_2000BP.SG 1087703
coverage: Shum_Laka.SG 1147190
coverage: Mende 769394
coverage: Nuer 565348
coverage: Ust_Ishim 1147829
coverage: Brazil_LapaDoSanto_9600BP 961887
coverage: Iron_Gates_HG 1141414
coverage: Yana 1149918
coverage: Tianyuan 844120
coverage: SunghirIV 1138519
coverage: GoyetQ116-1 765579
coverage: EHG 1027057
coverage: Taiwan_Hanben 1138853
coverage: IBM 1090734
coverage: Barcin_N 1137966
coverage: CHG 1149558
coverage: Ganj_Dareh_N 1057358
coverage: Jomon 935910
coverage: Paleo_Aleut 960525
coverage: Boisman_MN 1031750
coverage: Aeta 1060714
coverage: Onge 616424
dof (jackknife): 601.806
numsnps used: 44649
codimension 1
f4info:
f4rank: 4 dof: 18 chisq: 88.596 tail: 2.57751226e-11 dofdiff: 20 chisqdiff: -88.596 taildiff: 1
B:
scale 1.000 1.000 1.000 1.000
South_Africa_2000BP.SG -0.072 -0.528 -1.064 -1.544
Shum_Laka.SG -0.021 -0.247 0.008 -0.602
Mende -0.076 0.552 0.166 -0.183
Nuer -0.159 3.394 3.444 2.354
Ust_Ishim 0.962 -0.287 -1.669 0.381
Brazil_LapaDoSanto_9600BP 1.095 -0.621 -0.245 -0.651
Iron_Gates_HG 1.331 -1.083 0.019 0.179
Yana 1.048 -0.115 0.146 0.335
Tianyuan 0.978 0.038 0.171 0.109
SunghirIV 1.125 0.227 -0.623 0.461
GoyetQ116-1 1.169 -0.833 -0.177 0.274
EHG 1.234 0.200 0.221 -0.428
Taiwan_Hanben 1.001 -0.189 -0.700 -0.148
IBM 0.882 -0.258 -1.172 2.846
Barcin_N 1.500 -2.058 1.864 0.924
CHG 1.227 0.770 -0.182 -0.566
Ganj_Dareh_N 1.189 0.801 0.146 -0.514
Jomon 1.036 0.546 0.260 -0.098
Paleo_Aleut 1.044 0.755 0.059 -0.468
Boisman_MN 0.994 -0.753 -0.162 0.218
Aeta 0.931 0.562 0.307 -1.540
Onge 0.942 0.262 -0.166 -0.520
A:
scale 74.109 1530.519 3509.329 1830.186
Natufian 0.884 -1.272 -1.890 1.235
Levant_N 1.018 -1.435 0.909 -0.096
BedouinB 0.969 0.303 -0.024 -1.147
Dinka -1.122 -0.251 0.244 0.132
Mota.SG -0.992 -1.081 -0.737 -1.460


full rank
f4info:
f4rank: 5 dof: 0 chisq: 0.000 tail: 1 dofdiff: 18 chisqdiff: 88.596 taildiff: 2.57751226e-11
B:
scale 1.000 1.000 1.000 1.000 1.000
South_Africa_2000BP.SG -0.081 -1.263 -1.089 -1.075 -0.033
Shum_Laka.SG -0.015 -0.447 -0.344 -0.138 -0.880
Mende -0.073 -0.748 0.135 0.834 -0.827
Nuer -0.141 1.214 -0.520 3.932 1.582
Ust_Ishim 0.958 -0.447 1.742 -0.452 0.328
Brazil_LapaDoSanto_9600BP 1.091 -0.198 -0.473 -0.812 -0.134
Iron_Gates_HG 1.329 0.676 0.538 -0.807 -0.697
Yana 1.052 0.169 0.455 0.151 -0.515
Tianyuan 0.981 -0.250 0.467 0.323 -0.857
SunghirIV 1.123 0.176 0.654 0.057 0.737
GoyetQ116-1 1.173 0.350 0.529 -0.618 -0.364
EHG 1.235 -0.321 -0.659 0.076 0.118
Taiwan_Hanben 1.003 -0.298 0.850 -0.247 -0.263
IBM 0.869 2.566 2.272 -0.118 2.333
Barcin_N 1.493 2.661 0.375 -1.255 -2.497
CHG 1.235 -0.907 -0.400 0.474 0.472
Ganj_Dareh_N 1.197 -0.675 -0.985 0.513 0.789
Jomon 1.031 0.191 -0.834 0.236 1.115
Paleo_Aleut 1.049 -0.483 -0.784 0.406 0.712
Boisman_MN 0.991 0.340 1.048 -0.504 -1.015
Aeta 0.934 -1.270 -2.307 0.132 0.205
Onge 0.944 -0.316 -0.641 -0.081 0.569
A:
scale 75.668 2391.996 3296.374 1376.059 3625.366
Natufian 0.871 0.614 1.954 -1.331 0.627
Levant_N 1.029 0.791 -0.195 -0.932 -1.108
BedouinB 0.999 -1.525 -0.051 0.089 -1.018
Dinka -1.091 -0.536 0.890 0.569 -1.446
Mota.SG -0.997 -1.177 -0.591 -1.424 -0.502


best coefficients: 0.134 -0.010 0.429 0.615 -0.167
Jackknife mean: -0.654835121 0.522973947 0.624016147 0.409157023 0.098688004
std. errors: 0.296 0.344 0.116 0.059 0.077

error covariance (* 1000000)
87783 -98681 19777 4213 -13092
-98681 118415 -30398 -3471 14135
19777 -30398 13508 -67 -2820
4213 -3471 -67 3435 -4110
-13092 14135 -2820 -4110 5887


summ: Hadendowa 5 0.000000 -0.655 0.523 0.624 0.409 0.099 87783 -98681 19777 4213 -13092 118415 -30398 -3471 14135 13508 ...
-67 -2820 3435 -4110 5887

fixed pat wt dof chisq tail prob
00000 0 18 88.596 2.57751e-11 0.134 -0.010 0.429 0.615 -0.167 infeasible
00001 1 19 86.924 1.15783e-10 0.388 -0.356 0.523 0.445 -0.000 infeasible
00010 1 19 92.635 1.12829e-11 14.946 -17.380 4.272 0.411 -1.249 infeasible
00100 1 19 95.068 4.14508e-12 -2.455 2.815 0.000 0.743 -0.103 infeasible
01000 1 19 88.715 5.59918e-11 0.136 0.000 0.416 0.622 -0.174 infeasible
10000 1 19 87.082 1.08606e-10 0.000 0.122 0.422 0.623 -0.167 infeasible
00011 2 20 111.596 1.00419e-14 5.639 -6.866 2.227 -0.000 -0.000 infeasible
00101 2 20 95.774 7.1314e-12 -2.680 3.014 0.000 0.665 -0.000 infeasible
00110 2 20 117.973 6.76043e-16 -44.675 42.158 0.000 0.000 3.517 infeasible
01001 2 20 99.657 1.45084e-12 0.107 -0.000 0.425 0.468 -0.000
01010 2 20 160.780 5.30723e-24 -2.632 0.000 3.205 -0.000 0.427 infeasible
01100 2 20 128.753 6.6766e-18 0.551 0.000 0.000 0.712 -0.263 infeasible
10001 2 20 108.992 2.99775e-14 -0.000 0.048 0.484 0.469 -0.000
10010 2 20 137.226 1.69711e-19 -0.000 -3.270 4.111 -0.000 0.159 infeasible
10100 2 20 101.403 7.05856e-13 -0.000 0.514 0.000 0.711 -0.225 infeasible
11000 2 20 111.776 9.30782e-15 -0.000 0.000 0.554 0.597 -0.151 infeasible
00111 3 21 136.019 7.63863e-19 9.488 -8.488 0.000 -0.000 -0.000 infeasible
01011 3 21 170.485 2.07602e-25 -16.524 0.396 17.312 -0.015 -0.170 infeasible
01101 3 21 141.102 8.47926e-20 0.517 -0.000 0.000 0.483 -0.000
01110 3 21 272.206 0 0.434 0.000 0.000 -0.000 0.566
10011 3 21 204.552 0 0.000 -4.165 5.165 -0.000 -0.000 infeasible
10101 3 21 126.411 4.7024e-17 -0.000 0.487 0.000 0.513 -0.000
10110 3 21 258.265 0 -0.000 0.403 0.000 0.000 0.597
11001 3 21 122.797 2.1857e-16 0.000 -0.000 0.536 0.464 -0.000
11010 3 21 253.633 0 0.000 0.000 0.461 -0.000 0.539
11100 3 21 234.766 0 0.000 -0.000 0.000 -2.744 3.744 infeasible
01111 4 22 1392.578 0 1.000 0.000 0.000 -0.000 -0.000
10111 4 22 2481.224 0 0.000 1.000 0.000 -0.000 -0.000
11011 4 22 1657.061 0 0.000 0.000 1.000 -0.000 -0.000
11101 4 22 2356.303 0 0.000 0.000 0.000 1.000 -0.000
11110 4 22 983.523 0 0.000 0.000 0.000 -0.000 1.000

The Dstats are absolutely messed up when it comes to heavily admixed Eurasian + African + Basal sources. Even for modern populations. For example, I very strongly prefer Eurasians over Drobbah and Drobbah very strongly prefers Eurasians versus me. I think it might a result of expected heterozygosity rates. It also happens with the Pastoral neolithic sample.

[Mnemonics]

I fixed the link above. I've checked the uniparentals on there. I don't see anything really that we can say is without a doubt connected to SSA. It was L3 and K1 mtDNA and E2 for the one Y. I don't think any of these can be ruled out as being part of that group. A Basal group should straddle both Eurasian and Sub-Saharan in markers..or the overlap, if you will. I'm sure we can't also say zero flow ever occurred after the split and it is lost in bigger picture.

Those early pastoralists were likely part of two distinct populations one that seemed more Natufian like and one that had both more CHG/Iran_N affinities as well as more Iberomaurusian affinity (Late Halfan survivours?). I generally stick to using modern populations + Iberomaurusian in the right poplist when dealing with heavily admixed Africans because there is effect with damaged samples that generally disappears when you stick to transversion snps.

Here are some sucessful models using modern populations in the right poplist for those early pastoralists. Levant_BA is the Jordanian EBA samples.

Early Pastoralist Models 



Early Pastoralist 1: CHG Affinity 

ALLSNPS:YES

./qpAdm: parameter file: parqpAdm
### THE INPUT PARAMETERS
##PARAMETER NAME: VALUE
DIR: home/mnemonics/AdmixTools-master/bin
S1: qpdata
indivname: Nat6v8.ind
snpname: Nat6v8.snp
genotypename: Nat6v8.geno
popleft: left1
popright: right1
details: YES
allsnps: YES
## qpAdm version: 1201
seed: 1125138940
packed geno read OK
end of inpack

left pops:
Kenya_EarlyPastoralN1
Dinka
Mota
Levant_BA
Iberomaurusian4

right pops:
Khomani_San
Chukchi
Han
Abkhasian
Iranian
Sardinian
Luo
Estonian
Australian
Iberomaurusian

  0 Kenya_EarlyPastoralN1    1
  1                Dinka    1
  2                 Mota    1
  3            Levant_BA    3
  4      Iberomaurusian4    1
  5          Khomani_San    2
  6              Chukchi    1
  7                  Han    4
  8            Abkhasian    2
  9              Iranian    2
 10            Sardinian    4
 11                  Luo    2
 12             Estonian    2
 13           Australian    2
 14       Iberomaurusian    3
jackknife block size:     0.050
snps: 1135521  indivs: 31
number of blocks for block jackknife: 714
## ncols: 1135521
coverage: Kenya_EarlyPastoralN1 584384
coverage:                Dinka 1135118
coverage:                 Mota 1134612
coverage:            Levant_BA 870086
coverage:      Iberomaurusian4 953817
coverage:          Khomani_San 1106964
coverage:              Chukchi 1105918
coverage:                  Han 1135400
coverage:            Abkhasian 1107067
coverage:              Iranian 1107130
coverage:            Sardinian 1135401
coverage:                  Luo 1107058
coverage:             Estonian 1107090
coverage:           Australian 1106706
coverage:       Iberomaurusian 1069813
Effective number of blocks:   613.626
numsnps used: 1135521
codimension 1
f4info: 
f4rank: 3 dof:      6 chisq:     7.758 tail:          0.256412695 dofdiff:      8 chisqdiff:    -7.758 taildiff:                    1
B:
          scale     1.000     1.000     1.000 
        Chukchi     0.951     0.343    -0.160 
            Han     0.916     0.302    -0.003 
      Abkhasian     1.092     0.549    -0.224 
        Iranian     1.034     0.544    -0.290 
      Sardinian     1.213     0.595     0.086 
            Luo     0.080    -0.081     2.878 
       Estonian     1.095     0.519    -0.154 
     Australian     0.803     0.207     0.139 
 Iberomaurusian     1.293    -2.743    -0.712 
A:
          scale    99.671   231.350  2221.823 
          Dinka    -0.999    -0.350     1.533 
           Mota    -1.148    -0.322    -1.282 
      Levant_BA     1.085     0.601    -0.031 
Iberomaurusian4     0.711    -1.847     0.063 


full rank
f4info: 
f4rank: 4 dof:      0 chisq:     0.000 tail:                    1 dofdiff:      6 chisqdiff:     7.758 taildiff:          0.256412695
B:
          scale    95.710    84.732    89.701    91.393 
        Chukchi    -0.971    -0.960     1.037     0.383 
            Han    -0.949    -0.959     0.965     0.365 
      Abkhasian    -1.182    -1.162     1.186     0.293 
        Iranian    -1.128    -1.101     1.128     0.261 
      Sardinian    -1.264    -1.280     1.341     0.369 
            Luo     0.116    -0.221     0.056     0.116 
       Estonian    -1.176    -1.158     1.186     0.323 
     Australian    -0.814    -0.840     0.843     0.367 
 Iberomaurusian    -0.912    -0.928     0.629     2.860 
A:
          scale     2.000     2.000     2.000     2.000 
          Dinka     2.000     0.000     0.000     0.000 
           Mota     0.000     2.000     0.000     0.000 
      Levant_BA     0.000     0.000     2.000     0.000 
Iberomaurusian4     0.000     0.000     0.000     2.000 


best coefficients:     0.227     0.264     0.451     0.058 
Jackknife mean:      0.227421166     0.263721064     0.451129837     0.057727933 
      std. errors:     0.051     0.052     0.013     0.008 

error covariance (* 1,000,000)
      2571      -2543        -64         36 
     -2543       2662        -60        -59 
       -64        -60        163        -38 
        36        -59        -38         61 


summ: Kenya_EarlyPastoralN1    4      0.256413     0.227     0.264     0.451     0.058       2571      -2543        -64         36       2662   ...
       -60        -59        163        -38         61 

    fixed pat  wt  dof     chisq       tail prob
         0000  0     6     7.758        0.256413     0.227     0.264     0.451     0.058 
         0001  1     7    58.563     2.92078e-10     0.147     0.367     0.485     0.000 
         0010  1     7   257.946               0   -26.561    27.769     0.000    -0.209  infeasible
         0100  1     7    33.223     2.40591e-05     0.478     0.000     0.459     0.063 
         1000  1     7    35.538     8.85846e-06     0.000     0.491     0.455     0.054 
         0011  2     8   250.467               0   -18.774    19.774     0.000     0.000  infeasible
         0101  2     8    98.093     1.04696e-17     0.505     0.000     0.495     0.000 
         0110  2     8   987.743               0     0.849     0.000     0.000     0.151 
         1001  2     8    75.526     3.86977e-13     0.000     0.519     0.481     0.000 
         1010  2     8   920.258               0     0.000     0.852     0.000     0.148 
         1100  2     8  1336.774               0     0.000     0.000     0.888     0.112 
         0111  3     9  1301.712               0     1.000     0.000     0.000     0.000 
         1011  3     9  1142.427               0     0.000     1.000     0.000     0.000 
         1101  3     9  1501.786               0     0.000     0.000     1.000     0.000 
         1110  3     9  5024.226               0     0.000     0.000     0.000     1.000 
best pat:         0000         0.256413              -  -
best pat:         0100      2.40591e-05  chi(nested):    25.466 p-value for nested model:     4.50344e-07
best pat:         1001      3.86977e-13 not nested
best pat:         1011     3.24275e-240  chi(nested):  1066.901 p-value for nested model:    5.16745e-234

coeffs:     0.227     0.264     0.451     0.058 

## dscore:: f_4(Base, Fit, Rbase, right2)
## genstat:: f_4(Base, Fit, right1, right2)

details:                Dinka              Chukchi    -0.010141  -21.719070
details:                 Mota              Chukchi    -0.011334  -24.022433
details:            Levant_BA              Chukchi     0.011563   28.071124
details:      Iberomaurusian4              Chukchi     0.004186    8.811723
dscore:              Chukchi f4:     0.000161 Z:     0.425833

details:                Dinka                  Han    -0.009914  -22.137725
details:                 Mota                  Han    -0.011319  -25.661353
details:            Levant_BA                  Han     0.010759   27.390401
details:      Iberomaurusian4                  Han     0.003991    9.137601
dscore:                  Han f4:    -0.000158 Z:    -0.445182

details:                Dinka            Abkhasian    -0.012346  -26.767835
details:                 Mota            Abkhasian    -0.013719  -30.043447
details:            Levant_BA            Abkhasian     0.013227   33.528354
details:      Iberomaurusian4            Abkhasian     0.003210    7.223229
dscore:            Abkhasian f4:    -0.000276 Z:    -0.757234

details:                Dinka              Iranian    -0.011782  -25.874074
details:                 Mota              Iranian    -0.012989  -29.052460
details:            Levant_BA              Iranian     0.012576   31.978481
details:      Iberomaurusian4              Iranian     0.002861    6.562952
dscore:              Iranian f4:    -0.000269 Z:    -0.733574

details:                Dinka            Sardinian    -0.013211  -28.372565
details:                 Mota            Sardinian    -0.015104  -31.733638
details:            Levant_BA            Sardinian     0.014946   35.168904
details:      Iberomaurusian4            Sardinian     0.004040    8.500969
dscore:            Sardinian f4:    -0.000015 Z:    -0.038956

details:                Dinka                  Luo     0.001208    4.383617
details:                 Mota                  Luo    -0.002608   -9.623213
details:            Levant_BA                  Luo     0.000628    2.861308
details:      Iberomaurusian4                  Luo     0.001274    4.988747
dscore:                  Luo f4:    -0.000056 Z:    -0.284009

details:                Dinka             Estonian    -0.012292  -27.248355
details:                 Mota             Estonian    -0.013667  -30.366656
details:            Levant_BA             Estonian     0.013220   32.346512
details:      Iberomaurusian4             Estonian     0.003538    7.851477
dscore:             Estonian f4:    -0.000235 Z:    -0.629621

details:                Dinka           Australian    -0.008507  -19.428031
details:                 Mota           Australian    -0.009915  -22.261163
details:            Levant_BA           Australian     0.009399   24.721978
details:      Iberomaurusian4           Australian     0.004013    9.334870
dscore:           Australian f4:    -0.000080 Z:    -0.230876

details:                Dinka       Iberomaurusian    -0.009524  -22.407371
details:                 Mota       Iberomaurusian    -0.010957  -24.298256
details:            Levant_BA       Iberomaurusian     0.007008   18.350543
details:      Iberomaurusian4       Iberomaurusian     0.031289   63.390501
dscore:       Iberomaurusian f4:    -0.000090 Z:    -0.258646

gendstat:          Khomani_San              Chukchi     0.426
gendstat:          Khomani_San                  Han    -0.445
gendstat:          Khomani_San            Abkhasian    -0.757
gendstat:          Khomani_San              Iranian    -0.734
gendstat:          Khomani_San            Sardinian    -0.039
gendstat:          Khomani_San                  Luo    -0.284
gendstat:          Khomani_San             Estonian    -0.630
gendstat:          Khomani_San           Australian    -0.231
gendstat:          Khomani_San       Iberomaurusian    -0.259
gendstat:              Chukchi                  Han    -1.334
gendstat:              Chukchi            Abkhasian    -1.638
gendstat:              Chukchi              Iranian    -1.689
gendstat:              Chukchi            Sardinian    -0.701
gendstat:              Chukchi                  Luo    -0.596
gendstat:              Chukchi             Estonian    -1.554
gendstat:              Chukchi           Australian    -0.841
gendstat:              Chukchi       Iberomaurusian    -0.781
gendstat:                  Han            Abkhasian    -0.506
gendstat:                  Han              Iranian    -0.494
gendstat:                  Han            Sardinian     0.612
gendstat:                  Han                  Luo     0.304
gendstat:                  Han             Estonian    -0.328
gendstat:                  Han           Australian     0.320
gendstat:                  Han       Iberomaurusian     0.234
gendstat:            Abkhasian              Iranian     0.034
gendstat:            Abkhasian            Sardinian     1.276
gendstat:            Abkhasian                  Luo     0.631
gendstat:            Abkhasian             Estonian     0.194
gendstat:            Abkhasian           Australian     0.746
gendstat:            Abkhasian       Iberomaurusian     0.629
gendstat:              Iranian            Sardinian     1.226
gendstat:              Iranian                  Luo     0.612
gendstat:              Iranian             Estonian     0.161
gendstat:              Iranian           Australian     0.722
gendstat:              Iranian       Iberomaurusian     0.597
gendstat:            Sardinian                  Luo    -0.114
gendstat:            Sardinian             Estonian    -1.175
gendstat:            Sardinian           Australian    -0.244
gendstat:            Sardinian       Iberomaurusian    -0.255
gendstat:                  Luo             Estonian    -0.507
gendstat:                  Luo           Australian    -0.071
gendstat:                  Luo       Iberomaurusian    -0.107
gendstat:             Estonian           Australian     0.597
gendstat:             Estonian       Iberomaurusian     0.478
gendstat:           Australian       Iberomaurusian    -0.035

##end of qpAdm:      121.441 seconds cpu     1283.707 Mbytes in use


ALLSNPS:NO


./qpAdm: parameter file: parqpAdm
### THE INPUT PARAMETERS
##PARAMETER NAME: VALUE
DIR: home/mnemonics/AdmixTools-master/bin
S1: qpdata
indivname: Nat6v8.ind
snpname: Nat6v8.snp
genotypename: Nat6v8.geno
popleft: left1
popright: right1
details: YES
allsnps: NO
## qpAdm version: 1201
seed: 1125912536
packed geno read OK
end of inpack

left pops:
Kenya_EarlyPastoralN1
Dinka
Mota
Levant_BA
Iberomaurusian4

right pops:
Khomani_San
Chukchi
Han
Abkhasian
Iranian
Sardinian
Luo
Estonian
Australian
Iberomaurusian

  0 Kenya_EarlyPastoralN1    1
  1                Dinka    1
  2                 Mota    1
  3            Levant_BA    3
  4      Iberomaurusian4    1
  5          Khomani_San    2
  6              Chukchi    1
  7                  Han    4
  8            Abkhasian    2
  9              Iranian    2
 10            Sardinian    4
 11                  Luo    2
 12             Estonian    2
 13           Australian    2
 14       Iberomaurusian    3
jackknife block size:     0.050
snps: 1135521  indivs: 31
number of blocks for block jackknife: 714
## ncols: 1135521
coverage: Kenya_EarlyPastoralN1 584384
coverage:                Dinka 1135118
coverage:                 Mota 1134612
coverage:            Levant_BA 870086
coverage:      Iberomaurusian4 953817
coverage:          Khomani_San 1106964
coverage:              Chukchi 1105918
coverage:                  Han 1135400
coverage:            Abkhasian 1107067
coverage:              Iranian 1107130
coverage:            Sardinian 1135401
coverage:                  Luo 1107058
coverage:             Estonian 1107090
coverage:           Australian 1106706
coverage:       Iberomaurusian 1069813
Effective number of blocks:   618.136
numsnps used: 538521
codimension 1
f4info: 
f4rank: 3 dof:      6 chisq:     6.073 tail:          0.415022976 dofdiff:      8 chisqdiff:    -6.073 taildiff:                    1
B:
          scale     1.000     1.000     1.000 
        Chukchi     0.996     0.339    -0.126 
            Han     0.873     0.265    -0.030 
      Abkhasian     1.113     0.531    -0.210 
        Iranian     1.054     0.525    -0.341 
      Sardinian     1.143     0.522    -0.009 
            Luo     0.085    -0.079     2.888 
       Estonian     1.109     0.494    -0.133 
     Australian     0.829     0.205     0.107 
 Iberomaurusian     1.291    -2.773    -0.675 
A:
          scale    81.187   185.364  1743.764 
          Dinka    -0.974    -0.339     1.495 
           Mota    -1.130    -0.317    -1.323 
      Levant_BA     1.136     0.611    -0.071 
Iberomaurusian4     0.696    -1.847     0.089 


full rank
f4info: 
f4rank: 4 dof:      0 chisq:     0.000 tail:                    1 dofdiff:      6 chisqdiff:     6.073 taildiff:          0.415022976
B:
          scale    80.570    70.741    70.132    73.654 
        Chukchi    -1.018    -1.012     1.085     0.392 
            Han    -0.910    -0.919     0.914     0.340 
      Abkhasian    -1.201    -1.184     1.212     0.301 
        Iranian    -1.152    -1.119     1.149     0.266 
      Sardinian    -1.195    -1.205     1.257     0.350 
            Luo     0.120    -0.242     0.058     0.121 
       Estonian    -1.185    -1.169     1.208     0.331 
     Australian    -0.840    -0.867     0.871     0.370 
 Iberomaurusian    -0.903    -0.920     0.631     2.861 
A:
          scale     2.000     2.000     2.000     2.000 
          Dinka     2.000     0.000     0.000     0.000 
           Mota     0.000     2.000     0.000     0.000 
      Levant_BA     0.000     0.000     2.000     0.000 
Iberomaurusian4     0.000     0.000     0.000     2.000 


best coefficients:     0.248     0.260     0.438     0.055 
Jackknife mean:      0.247561628     0.260038907     0.437568330     0.054831135 
      std. errors:     0.053     0.054     0.013     0.008 

error covariance (* 1,000,000)
      2820      -2789        -73         43 
     -2789       2908        -52        -67 
       -73        -52        163        -38 
        43        -67        -38         62 


summ: Kenya_EarlyPastoralN1    4      0.415023     0.248     0.260     0.438     0.055       2820      -2789        -73         43       2908   ...
       -52        -67        163        -38         62 

    fixed pat  wt  dof     chisq       tail prob
         0000  0     6     6.073        0.415023     0.248     0.260     0.438     0.055 
         0001  1     7    50.796     1.00783e-08     0.172     0.358     0.470     0.000 
         0010  1     7   241.490               0   -24.994    26.123     0.000    -0.129  infeasible
         0100  1     7    29.213     0.000132277     0.496     0.000     0.444     0.060 
         1000  1     7    34.738     1.25255e-05     0.000     0.508     0.442     0.051 
         0011  2     8   236.820               0   -20.243    21.243     0.000     0.000  infeasible
         0101  2     8    87.274     1.66072e-15     0.524     0.000     0.476     0.000 
         0110  2     8   952.658               0     0.850     0.000     0.000     0.150 
         1001  2     8    69.052     7.58755e-12     0.000     0.534     0.466     0.000 
         1010  2     8   902.285               0     0.000     0.853     0.000     0.147 
         1100  2     8  1339.992               0     0.000     0.000     0.881     0.119 
         0111  3     9  1242.076               0     1.000     0.000     0.000     0.000 
         1011  3     9  1125.498               0     0.000     1.000     0.000     0.000 
         1101  3     9  1518.801               0     0.000     0.000     1.000     0.000 
         1110  3     9  4880.098               0     0.000     0.000     0.000     1.000 
best pat:         0000         0.415023              -  -
best pat:         0100      0.000132277  chi(nested):    23.140 p-value for nested model:     1.50618e-06
best pat:         1001      7.58755e-12 not nested
best pat:         1011     1.46014e-236  chi(nested):  1056.446 p-value for nested model:    9.67577e-232

coeffs:     0.248     0.260     0.438     0.055 

## dscore:: f_4(Base, Fit, Rbase, right2)
## genstat:: f_4(Base, Fit, right1, right2)

details:                Dinka              Chukchi    -0.012630  -21.493130
details:                 Mota              Chukchi    -0.014312  -24.205009
details:            Levant_BA              Chukchi     0.015469   28.108089
details:      Iberomaurusian4              Chukchi     0.005322    8.639280
dscore:              Chukchi f4:     0.000210 Z:     0.431121

details:                Dinka                  Han    -0.011290  -22.022719
details:                 Mota                  Han    -0.012996  -25.698979
details:            Levant_BA                  Han     0.013034   27.430145
details:      Iberomaurusian4                  Han     0.004618    8.966534
dscore:                  Han f4:    -0.000219 Z:    -0.525951

details:                Dinka            Abkhasian    -0.014906  -26.412352
details:                 Mota            Abkhasian    -0.016731  -29.802429
details:            Levant_BA            Abkhasian     0.017284   33.691934
details:      Iberomaurusian4            Abkhasian     0.004085    7.193882
dscore:            Abkhasian f4:    -0.000256 Z:    -0.553188

details:                Dinka              Iranian    -0.014301  -25.731224
details:                 Mota              Iranian    -0.015822  -28.799385
details:            Levant_BA              Iranian     0.016388   31.758200
details:      Iberomaurusian4              Iranian     0.003615    6.464201
dscore:              Iranian f4:    -0.000287 Z:    -0.615518

details:                Dinka            Sardinian    -0.014828  -28.090119
details:                 Mota            Sardinian    -0.017028  -31.429963
details:            Levant_BA            Sardinian     0.017917   35.219504
details:      Iberomaurusian4            Sardinian     0.004746    8.471124
dscore:            Sardinian f4:    -0.000000 Z:    -0.000546

details:                Dinka                  Luo     0.001489    4.154148
details:                 Mota                  Luo    -0.003414   -9.632898
details:            Levant_BA                  Luo     0.000831    2.737599
details:      Iberomaurusian4                  Luo     0.001642    4.752155
dscore:                  Luo f4:    -0.000065 Z:    -0.242973

details:                Dinka             Estonian    -0.014709  -26.793184
details:                 Mota             Estonian    -0.016531  -30.004168
details:            Levant_BA             Estonian     0.017227   32.489170
details:      Iberomaurusian4             Estonian     0.004497    7.792758
dscore:             Estonian f4:    -0.000157 Z:    -0.335303

details:                Dinka           Australian    -0.010421  -19.173507
details:                 Mota           Australian    -0.012260  -22.122193
details:            Levant_BA           Australian     0.012413   24.608522
details:      Iberomaurusian4           Australian     0.005029    8.940339
dscore:           Australian f4:    -0.000062 Z:    -0.138609

details:                Dinka       Iberomaurusian    -0.011211  -21.668535
details:                 Mota       Iberomaurusian    -0.013011  -23.823674
details:            Levant_BA       Iberomaurusian     0.008991   18.238012
details:      Iberomaurusian4       Iberomaurusian     0.038844   62.922907
dscore:       Iberomaurusian f4:    -0.000097 Z:    -0.221402

gendstat:          Khomani_San              Chukchi     0.431
gendstat:          Khomani_San                  Han    -0.526
gendstat:          Khomani_San            Abkhasian    -0.553
gendstat:          Khomani_San              Iranian    -0.616
gendstat:          Khomani_San            Sardinian    -0.001
gendstat:          Khomani_San                  Luo    -0.243
gendstat:          Khomani_San             Estonian    -0.335
gendstat:          Khomani_San           Australian    -0.139
gendstat:          Khomani_San       Iberomaurusian    -0.221
gendstat:              Chukchi                  Han    -1.414
gendstat:              Chukchi            Abkhasian    -1.339
gendstat:              Chukchi              Iranian    -1.522
gendstat:              Chukchi            Sardinian    -0.679
gendstat:              Chukchi                  Luo    -0.580
gendstat:              Chukchi             Estonian    -1.122
gendstat:              Chukchi           Australian    -0.736
gendstat:              Chukchi       Iberomaurusian    -0.739
gendstat:                  Han            Abkhasian    -0.123
gendstat:                  Han              Iranian    -0.240
gendstat:                  Han            Sardinian     0.796
gendstat:                  Han                  Luo     0.384
gendstat:                  Han             Estonian     0.213
gendstat:                  Han           Australian     0.519
gendstat:                  Han       Iberomaurusian     0.345
gendstat:            Abkhasian              Iranian    -0.116
gendstat:            Abkhasian            Sardinian     1.009
gendstat:            Abkhasian                  Luo     0.429
gendstat:            Abkhasian             Estonian     0.358
gendstat:            Abkhasian           Australian     0.575
gendstat:            Abkhasian       Iberomaurusian     0.421
gendstat:              Iranian            Sardinian     1.135
gendstat:              Iranian                  Luo     0.498
gendstat:              Iranian             Estonian     0.471
gendstat:              Iranian           Australian     0.668
gendstat:              Iranian       Iberomaurusian     0.501
gendstat:            Sardinian                  Luo    -0.151
gendstat:            Sardinian             Estonian    -0.686
gendstat:            Sardinian           Australian    -0.192
gendstat:            Sardinian       Iberomaurusian    -0.270
gendstat:                  Luo             Estonian    -0.207
gendstat:                  Luo           Australian     0.007
gendstat:                  Luo       Iberomaurusian    -0.080
gendstat:             Estonian           Australian     0.290
gendstat:             Estonian       Iberomaurusian     0.158
gendstat:           Australian       Iberomaurusian    -0.093

##end of qpAdm:      124.010 seconds cpu     1283.707 Mbytes in use














Early Pastoralist 2: First Wave Pastoralist


ALL SNPS: YES

left pops:
Kenya_EarlyPastoralN2
Dinka
Mota
Natufian

right pops:
Khomani_San
Chukchi
Han
Abkhasian
Iranian
Sardinian
Luo
Estonian
Australian
Iberomaurusian

  0 Kenya_EarlyPastoralN2    1
  1                Dinka    1
  2                 Mota    1
  3             Natufian    6
  4          Khomani_San    2
  5              Chukchi    1
  6                  Han    4
  7            Abkhasian    2
  8              Iranian    2
  9            Sardinian    4
 10                  Luo    2
 11             Estonian    2
 12           Australian    2
 13       Iberomaurusian    3
jackknife block size:     0.050
snps: 1135520  indivs: 33
number of blocks for block jackknife: 714
## ncols: 1135520
coverage: Kenya_EarlyPastoralN2 495701
coverage:                Dinka 1135118
coverage:                 Mota 1134612
coverage:             Natufian 529354
coverage:          Khomani_San 1106964
coverage:              Chukchi 1105918
coverage:                  Han 1135400
coverage:            Abkhasian 1107067
coverage:              Iranian 1107130
coverage:            Sardinian 1135401
coverage:                  Luo 1107058
coverage:             Estonian 1107090
coverage:           Australian 1106706
coverage:       Iberomaurusian 1069813
Effective number of blocks:   611.438
numsnps used: 1135520
codimension 1
f4info: 
f4rank: 2 dof:      7 chisq:     5.851 tail:           0.55724894 dofdiff:      9 chisqdiff:    -5.851 taildiff:                    1
B:
          scale     1.000     1.000 
        Chukchi     0.989    -0.232 
            Han     0.956    -0.054 
      Abkhasian     1.131    -0.275 
        Iranian     1.083    -0.409 
      Sardinian     1.330    -0.225 
            Luo     0.083     2.926 
       Estonian     1.156    -0.293 
     Australian     0.822     0.040 
 Iberomaurusian     0.931    -0.044 
A:
          scale   104.837  2192.044 
          Dinka    -1.060     1.467 
           Mota    -1.216    -0.920 
       Natufian     0.631     0.035 


full rank
f4info: 
f4rank: 3 dof:      0 chisq:     0.000 tail:                    1 dofdiff:      7 chisqdiff:     5.851 taildiff:           0.55724894
B:
          scale    96.309    85.401   166.075 
        Chukchi    -0.982    -0.975     1.013 
            Han    -0.934    -0.944     0.997 
      Abkhasian    -1.143    -1.134     1.110 
        Iranian    -1.096    -1.076     1.075 
      Sardinian    -1.322    -1.323     1.338 
            Luo     0.103    -0.195     0.090 
       Estonian    -1.174    -1.160     1.128 
     Australian    -0.812    -0.831     0.826 
 Iberomaurusian    -0.926    -0.944     0.914 
A:
          scale     1.732     1.732     1.732 
          Dinka     1.732     0.000     0.000 
           Mota     0.000     1.732     0.000 
       Natufian     0.000     0.000     1.732 


best coefficients:     0.126     0.226     0.648 
Jackknife mean:      0.126448069     0.225663054     0.647888877 
      std. errors:     0.049     0.051     0.013 

error covariance (* 1,000,000)
      2392      -2420         28 
     -2420       2609       -190 
        28       -190        162 


summ: Kenya_EarlyPastoralN2    3      0.557249     0.126     0.226     0.648       2392      -2420         28       2609       -190   ...
       162 

    fixed pat  wt  dof     chisq       tail prob
          000  0     7     5.851        0.557249     0.126     0.226     0.648 
          001  1     8   227.693               0   -19.456    20.456     0.000  infeasible
          010  1     8    29.612      0.00024749     0.333     0.000     0.667 
          100  1     8    14.280        0.074749     0.000     0.356     0.644 
          011  2     9  1454.962               0     1.000     0.000     0.000 
          101  2     9  1269.031               0     0.000     1.000     0.000 
          110  2     9   725.423               0     0.000     0.000     1.000 
best pat:          000         0.557249              -  -
best pat:          100         0.074749  chi(nested):     8.429 p-value for nested model:      0.00369254
best pat:          110     2.36331e-150  chi(nested):   711.142 p-value for nested model:    1.13074e-156

coeffs:     0.126     0.226     0.648 

## dscore:: f_4(Base, Fit, Rbase, right2)
## genstat:: f_4(Base, Fit, right1, right2)

details:                Dinka              Chukchi    -0.010193  -24.033680
details:                 Mota              Chukchi    -0.011420  -25.983020
details:             Natufian              Chukchi     0.006102   20.064108
dscore:              Chukchi f4:     0.000085 Z:     0.290171

details:                Dinka                  Han    -0.009702  -22.949267
details:                 Mota                  Han    -0.011051  -25.456278
details:             Natufian                  Han     0.006005   18.976100
dscore:                  Han f4:     0.000168 Z:     0.554310

details:                Dinka            Abkhasian    -0.011867  -27.697878
details:                 Mota            Abkhasian    -0.013277  -30.142758
details:             Natufian            Abkhasian     0.006685   22.168319
dscore:            Abkhasian f4:    -0.000168 Z:    -0.568141

details:                Dinka              Iranian    -0.011384  -26.723765
details:                 Mota              Iranian    -0.012600  -30.163240
details:             Natufian              Iranian     0.006473   22.286736
dscore:              Iranian f4:    -0.000092 Z:    -0.317640

details:                Dinka            Sardinian    -0.013732  -29.068780
details:                 Mota            Sardinian    -0.015490  -32.291955
details:             Natufian            Sardinian     0.008060   23.378637
dscore:            Sardinian f4:    -0.000013 Z:    -0.039274

details:                Dinka                  Luo     0.001066    4.034555
details:                 Mota                  Luo    -0.002281   -8.682469
details:             Natufian                  Luo     0.000543    3.001278
dscore:                  Luo f4:    -0.000029 Z:    -0.169122

details:                Dinka             Estonian    -0.012188  -28.344959
details:                 Mota             Estonian    -0.013580  -31.559059
details:             Natufian             Estonian     0.006794   22.021371
dscore:             Estonian f4:    -0.000207 Z:    -0.683692

details:                Dinka           Australian    -0.008432  -20.994686
details:                 Mota           Australian    -0.009733  -23.813598
details:             Natufian           Australian     0.004975   16.945158
dscore:           Australian f4:    -0.000041 Z:    -0.148217

details:                Dinka       Iberomaurusian    -0.009619  -24.004156
details:                 Mota       Iberomaurusian    -0.011052  -26.229832
details:             Natufian       Iberomaurusian     0.005501   18.443171
dscore:       Iberomaurusian f4:    -0.000149 Z:    -0.525405

gendstat:          Khomani_San              Chukchi     0.290
gendstat:          Khomani_San                  Han     0.554
gendstat:          Khomani_San            Abkhasian    -0.568
gendstat:          Khomani_San              Iranian    -0.318
gendstat:          Khomani_San            Sardinian    -0.039
gendstat:          Khomani_San                  Luo    -0.169
gendstat:          Khomani_San             Estonian    -0.684
gendstat:          Khomani_San           Australian    -0.148
gendstat:          Khomani_San       Iberomaurusian    -0.525
gendstat:              Chukchi                  Han     0.395
gendstat:              Chukchi            Abkhasian    -1.150
gendstat:              Chukchi              Iranian    -0.823
gendstat:              Chukchi            Sardinian    -0.432
gendstat:              Chukchi                  Luo    -0.412
gendstat:              Chukchi             Estonian    -1.317
gendstat:              Chukchi           Australian    -0.549
gendstat:              Chukchi       Iberomaurusian    -0.885
gendstat:                  Han            Abkhasian    -1.575
gendstat:                  Han              Iranian    -1.281
gendstat:                  Han            Sardinian    -0.849
gendstat:                  Han                  Luo    -0.736
gendstat:                  Han             Estonian    -1.810
gendstat:                  Han           Australian    -1.032
gendstat:                  Han       Iberomaurusian    -1.272
gendstat:            Abkhasian              Iranian     0.441
gendstat:            Abkhasian            Sardinian     0.847
gendstat:            Abkhasian                  Luo     0.525
gendstat:            Abkhasian             Estonian    -0.204
gendstat:            Abkhasian           Australian     0.584
gendstat:            Abkhasian       Iberomaurusian     0.080
gendstat:              Iranian            Sardinian     0.429
gendstat:              Iranian                  Luo     0.247
gendstat:              Iranian             Estonian    -0.623
gendstat:              Iranian           Australian     0.236
gendstat:              Iranian       Iberomaurusian    -0.240
gendstat:            Sardinian                  Luo    -0.051
gendstat:            Sardinian             Estonian    -1.050
gendstat:            Sardinian           Australian    -0.124
gendstat:            Sardinian       Iberomaurusian    -0.518
gendstat:                  Luo             Estonian    -0.641
gendstat:                  Luo           Australian    -0.049
gendstat:                  Luo       Iberomaurusian    -0.473
gendstat:             Estonian           Australian     0.732
gendstat:             Estonian       Iberomaurusian     0.225
gendstat:           Australian       Iberomaurusian    -0.437


ALLSNPS: NO


left pops:
Kenya_EarlyPastoralN2
Dinka
Mota
Natufian

right pops:
Khomani_San
Chukchi
Han
Abkhasian
Iranian
Sardinian
Luo
Estonian
Australian
Iberomaurusian

  0 Kenya_EarlyPastoralN2    1
  1                Dinka    1
  2                 Mota    1
  3             Natufian    6
  4          Khomani_San    2
  5              Chukchi    1
  6                  Han    4
  7            Abkhasian    2
  8              Iranian    2
  9            Sardinian    4
 10                  Luo    2
 11             Estonian    2
 12           Australian    2
 13       Iberomaurusian    3
jackknife block size:     0.050
snps: 1135520  indivs: 33
number of blocks for block jackknife: 714
## ncols: 1135520
coverage: Kenya_EarlyPastoralN2 495701
coverage:                Dinka 1135118
coverage:                 Mota 1134612
coverage:             Natufian 529354
coverage:          Khomani_San 1106964
coverage:              Chukchi 1105918
coverage:                  Han 1135400
coverage:            Abkhasian 1107067
coverage:              Iranian 1107130
coverage:            Sardinian 1135401
coverage:                  Luo 1107058
coverage:             Estonian 1107090
coverage:           Australian 1106706
coverage:       Iberomaurusian 1069813
Effective number of blocks:   616.165
numsnps used: 358299
codimension 1
f4info: 
f4rank: 2 dof:      7 chisq:     5.648 tail:          0.581440463 dofdiff:      9 chisqdiff:    -5.648 taildiff:                    1
B:
          scale     1.000     1.000 
        Chukchi     1.048    -0.313 
            Han     0.895     0.079 
      Abkhasian     1.158    -0.278 
        Iranian     1.112    -0.582 
      Sardinian     1.237    -0.175 
            Luo     0.069     2.877 
       Estonian     1.179    -0.356 
     Australian     0.868     0.152 
 Iberomaurusian     0.920    -0.141 
A:
          scale    87.811  1724.349 
          Dinka    -0.971     1.375 
           Mota    -1.158    -1.047 
       Natufian     0.845     0.108 


full rank
f4info: 
f4rank: 3 dof:      0 chisq:     0.000 tail:                    1 dofdiff:      7 chisqdiff:     5.648 taildiff:          0.581440463
B:
          scale    88.765    76.352   102.438 
        Chukchi    -1.038    -1.022     1.088 
            Han    -0.874    -0.902     0.908 
      Abkhasian    -1.161    -1.153     1.152 
        Iranian    -1.124    -1.087     1.117 
      Sardinian    -1.253    -1.259     1.199 
            Luo     0.142    -0.196     0.101 
       Estonian    -1.193    -1.175     1.167 
     Australian    -0.837    -0.878     0.877 
 Iberomaurusian    -0.913    -0.925     0.915 
A:
          scale     1.732     1.732     1.732 
          Dinka     1.732     0.000     0.000 
           Mota     0.000     1.732     0.000 
       Natufian     0.000     0.000     1.732 


best coefficients:     0.164     0.273     0.563 
Jackknife mean:      0.163782426     0.273392915     0.562824660 
      std. errors:     0.064     0.066     0.014 

error covariance (* 1,000,000)
      4121      -4132         11 
     -4132       4347       -216 
        11       -216        205 


summ: Kenya_EarlyPastoralN2    3      0.581440     0.164     0.273     0.563       4121      -4132         11       4347       -216   ...
       205 

    fixed pat  wt  dof     chisq       tail prob
          000  0     7     5.648         0.58144     0.164     0.273     0.563 
          001  1     8   183.163               0   -27.849    28.849     0.000  infeasible
          010  1     8    26.025      0.00104006     0.420     0.000     0.580 
          100  1     8    13.965       0.0826871     0.000     0.439     0.561 
          011  2     9  1219.431               0     1.000     0.000     0.000 
          101  2     9  1126.813               0     0.000     1.000     0.000 
          110  2     9   732.193               0     0.000     0.000     1.000 
best pat:          000          0.58144              -  -
best pat:          100        0.0826871  chi(nested):     8.317 p-value for nested model:      0.00392719
best pat:          110     8.26706e-152  chi(nested):   718.228 p-value for nested model:    3.25447e-158

coeffs:     0.164     0.273     0.563 

## dscore:: f_4(Base, Fit, Rbase, right2)
## genstat:: f_4(Base, Fit, right1, right2)

details:                Dinka              Chukchi    -0.011695  -21.471213
details:                 Mota              Chukchi    -0.013379  -23.686087
details:             Natufian              Chukchi     0.010620   20.138619
dscore:              Chukchi f4:     0.000405 Z:     0.879311

details:                Dinka                  Han    -0.009848  -20.554844
details:                 Mota                  Han    -0.011810  -23.793784
details:             Natufian                  Han     0.008865   19.008466
dscore:                  Han f4:     0.000149 Z:     0.360813

details:                Dinka            Abkhasian    -0.013079  -24.799468
details:                 Mota            Abkhasian    -0.015098  -28.084816
details:             Natufian            Abkhasian     0.011242   22.192984
dscore:            Abkhasian f4:     0.000059 Z:     0.131844

details:                Dinka              Iranian    -0.012661  -23.763407
details:                 Mota              Iranian    -0.014239  -27.611374
details:             Natufian              Iranian     0.010909   22.466003
dscore:              Iranian f4:     0.000175 Z:     0.397817

details:                Dinka            Sardinian    -0.014121  -26.339607
details:                 Mota            Sardinian    -0.016490  -30.855983
details:             Natufian            Sardinian     0.011702   23.509050
dscore:            Sardinian f4:    -0.000233 Z:    -0.515981

details:                Dinka                  Luo     0.001598    4.481091
details:                 Mota                  Luo    -0.002569   -7.088715
details:             Natufian                  Luo     0.000981    2.997121
dscore:                  Luo f4:     0.000112 Z:     0.394016

details:                Dinka             Estonian    -0.013435  -25.187222
details:                 Mota             Estonian    -0.015392  -28.743309
details:             Natufian             Estonian     0.011397   22.141313
dscore:             Estonian f4:     0.000007 Z:     0.016159

details:                Dinka           Australian    -0.009426  -18.581395
details:                 Mota           Australian    -0.011505  -22.585127
details:             Natufian           Australian     0.008560   17.002049
dscore:           Australian f4:     0.000130 Z:     0.300388

details:                Dinka       Iberomaurusian    -0.010288  -20.175505
details:                 Mota       Iberomaurusian    -0.012118  -23.285897
details:             Natufian       Iberomaurusian     0.008936   18.450243
dscore:       Iberomaurusian f4:     0.000033 Z:     0.077744

gendstat:          Khomani_San              Chukchi     0.879
gendstat:          Khomani_San                  Han     0.361
gendstat:          Khomani_San            Abkhasian     0.132
gendstat:          Khomani_San              Iranian     0.398
gendstat:          Khomani_San            Sardinian    -0.516
gendstat:          Khomani_San                  Luo     0.394
gendstat:          Khomani_San             Estonian     0.016
gendstat:          Khomani_San           Australian     0.300
gendstat:          Khomani_San       Iberomaurusian     0.078
gendstat:              Chukchi                  Han    -0.817
gendstat:              Chukchi            Abkhasian    -1.010
gendstat:              Chukchi              Iranian    -0.697
gendstat:              Chukchi            Sardinian    -1.963
gendstat:              Chukchi                  Luo    -0.672
gendstat:              Chukchi             Estonian    -1.145
gendstat:              Chukchi           Australian    -0.764
gendstat:              Chukchi       Iberomaurusian    -0.910
gendstat:                  Han            Abkhasian    -0.288
gendstat:                  Han              Iranian     0.088
gendstat:                  Han            Sardinian    -1.331
gendstat:                  Han                  Luo    -0.098
gendstat:                  Han             Estonian    -0.465
gendstat:                  Han           Australian    -0.064
gendstat:                  Han       Iberomaurusian    -0.326
gendstat:            Abkhasian              Iranian     0.433
gendstat:            Abkhasian            Sardinian    -1.125
gendstat:            Abkhasian                  Luo     0.132
gendstat:            Abkhasian             Estonian    -0.176
gendstat:            Abkhasian           Australian     0.210
gendstat:            Abkhasian       Iberomaurusian    -0.071
gendstat:              Iranian            Sardinian    -1.615
gendstat:              Iranian                  Luo    -0.162
gendstat:              Iranian             Estonian    -0.589
gendstat:              Iranian           Australian    -0.136
gendstat:              Iranian       Iberomaurusian    -0.389
gendstat:            Sardinian                  Luo     0.832
gendstat:            Sardinian             Estonian     0.923
gendstat:            Sardinian           Australian     1.134
gendstat:            Sardinian       Iberomaurusian     0.730
gendstat:                  Luo             Estonian    -0.246
gendstat:                  Luo           Australian     0.044
gendstat:                  Luo       Iberomaurusian    -0.206
gendstat:             Estonian           Australian     0.347
gendstat:             Estonian       Iberomaurusian     0.065
gendstat:           Australian       Iberomaurusian    -0.258

##end of qpAdm:      115.304 seconds cpu     1247.232 Mbytes in use