Global25 automated nMonte for South/Central Asian members

[ThaYamamoto]

Don't you think that Simulated_AASI_by_DMXX inflates the AASI a little bit (3-4%)? This is what Kashmiri Pandit average scores on Genoplot (penalty off) with this particular model:

sample: Kashmiri Pandit:Average
distance: 1.8314
Ganj_Dareh_N: 31
Simulated_AASI_by_DMXX: 25.5
Sidelkino_HG: 9
Barcin_N: 20
Tyumen_HG: 14.5

penalty on:

sample: Kashmiri Pandit:Average
distance: 2.9794
Ganj_Dareh_N: 45
Simulated_AASI_by_DMXX: 23.5
Barcin_N: 15
Tyumen_HG: 8.5
Sidelkino_HG: 8

On other models the AASI for KPs limits itself to 20-21%. For me it has typically been at 24-26%. Or am I reading too much into it?

Some other groups (penalty on):

sample: Brahmin Gujarat:Average
distance: 2.1267
Ganj_Dareh_N: 40.5
Simulated_AASI_by_DMXX: 30
Barcin_N: 14
Tyumen_HG: 9.5
Sidelkino_HG: 6

sample: Bihar Brahmin Bhumihar:mean
distance: 3.1936
Ganj_Dareh_N: 36.5
Simulated_AASI_by_DMXX: 30
Barcin_N: 15
Tyumen_HG: 13
Sidelkino_HG: 5.5

sample: Brahmin Uttar Pradesh:Average
distance: 3.2536
Ganj_Dareh_N: 35.5
Simulated_AASI_by_DMXX: 34.5
Barcin_N: 12
Tyumen_HG: 10.5
Sidelkino_HG: 7.5

Hmm I think something in both our models is off or different from whatever pegasus is using primarily because of Barcin's inflation. Maybe we both are using older sims?

[Kirtan24]

Hmm I think something in both our models is off or different from whatever pegasus is using primarily because of Barcin's inflation. Maybe we both are using older sims?

I just used the sims on Genoplot, so they should be up to date.

[ThaYamamoto]

I just used the sims on Genoplot, so they should be up to date.

Aite in that case gonna have to see what pegasus says.

[pegasus]

Don't you think that Simulated_AASI_by_DMXX inflates the AASI a little bit (3-4%)? This is what Kashmiri Pandit average scores on Genoplot (penalty off) with this particular model:

sample: Kashmiri Pandit:Average
distance: 1.8314
Ganj_Dareh_N: 31
Simulated_AASI_by_DMXX: 25.5
Sidelkino_HG: 9
Barcin_N: 20
Tyumen_HG: 14.5

penalty on:

sample: Kashmiri Pandit:Average
distance: 2.9794
Ganj_Dareh_N: 45
Simulated_AASI_by_DMXX: 23.5
Barcin_N: 15
Tyumen_HG: 8.5
Sidelkino_HG: 8

On other models the AASI for KPs limits itself to 20-21%. For me it has typically been at 24-26%. Or am I reading too much into it?

Some other groups (penalty on):

sample: Brahmin Gujarat:Average
distance: 2.1267
Ganj_Dareh_N: 40.5
Simulated_AASI_by_DMXX: 30
Barcin_N: 14
Tyumen_HG: 9.5
Sidelkino_HG: 6

sample: Bihar Brahmin Bhumihar:mean
distance: 3.1936
Ganj_Dareh_N: 36.5
Simulated_AASI_by_DMXX: 30
Barcin_N: 15
Tyumen_HG: 13
Sidelkino_HG: 5.5

sample: Brahmin Uttar Pradesh:Average
distance: 3.2536
Ganj_Dareh_N: 35.5
Simulated_AASI_by_DMXX: 34.5
Barcin_N: 12
Tyumen_HG: 10.5
Sidelkino_HG: 7.5

Kashmiri pandits have Tibetan related admixture, pretty much all Himalayan populations do. There is 2-4% SE but its within range till they find actual HGs. Penalty =0 does inflates AASI and deflates Iran_N a bit . Here with default penalty, with better outgroups it's not too different though.


sample: Kirtan
distance: 2.439
Ganj_Dareh_N: 44.5
Simulated_AASI_by_DMXX: 27.5
Karelia_HG: 8
Barcin_N: 8.5
Tyumen_HG: 9
GEO_CHG: 2.5

[Rahuls77]

What is the age of the Tyumen_HG sample?

While it is definitely a site which has importance for the infusion of Steppe ancestry in South Asia, from late bronze age to Iron age onward, however if we try going back to the any older samples, such as early bronze or late neolithic, especially from the Eurasia, we might have a better chance instead with South Asian samples for the period, for instance Chokhopani and Shahr e Sohta 2 samples. For that is has been the source of most South Asian ancestry from the Himalayas and among many groups, such as the older Gujarati Brahmin G25 samples, minus Kirtan, because the caste identities for these groups had not solidified anytime before 600-800 AD, for the GBs, and much later for the KPs. Speaking of Chokhopani, even many Punjabis show NE Asian, which likely derived from a Chokhopani-like population that might have trickled down from Tibet. And for the GBs there might have been some infusion of it from the Himalayas, ranging from the NW to the Uttarakhand area, during medieval and the period immediately before it, of the Indian History.

Here is what I get on Vahaduo, without using simulated AASI coordinates. All groups prefer Sintashta/Chokhopani over Tyumen HG.

Distance: 3.1667% / 0.03166696
Target: KPB_Scaled
69.7 IRN_Shahr_I_Sokhta_BA2
21.0 RUS_Srubnaya_MLBA
5.0 TUR_Barcin_N
4.3 NPL_Chokhopani_2700BP

Distance: 2.5378% / 0.02537828
Target: Kashmiri_Pandit
67.6 IRN_Shahr_I_Sokhta_BA2
25.1 RUS_Srubnaya_MLBA
5.5 NPL_Chokhopani_2700BP
1.6 TUR_Barcin_N
0.2 RUS_Tyumen_HG

Distance: 2.2224% / 0.02222437
Target: Brahmin_Gujarat
76.4 IRN_Shahr_I_Sokhta_BA2
16.1 RUS_Srubnaya_MLBA
3.8 NPL_Chokhopani_2700BP
1.9 RUS_Tyumen_HG
1.8 TUR_Barcin_N

[pegasus]

Another interesting qpAdm , this is one of the Ghaznavids 7716, he surprisingly needed a Levantine source-based of the stats . On G25 looked similar to other Pashtuns but he is not typical at all of them ,given his excess Levantine-like ancestry,. His Y DNA is not Pashtun like at all either. Though his higher IVC ancestry ties him to the region, so my guess he was a warrior or a religious figure who had both local and foreign origins. The only vector to my mind which would have brought Levantine type ancestry would be via the Saffarids . He came out 25% Steppe related, 35% IVC related ,25% BMAC, 16% Caananite. Its a good working model, but more genomes would be needed to properly resolve this. The usual models failed miserably.

left pops:
Pakistan_Medieval_Udegram_Ghaznavid
ShahrISokhtaSubset
Kazakhstan_MLBA_OyDzhaylau
Alalakh_MLBA_outlier
Levant_BA

right pops:
Cameroon_SMA.DG
Russia_Steppe_Eneolithic
ONG.SG
PPNB
Iran_GanjDareh_N
DevilsCave_N.SG
Russia_UstBelaya_Angara
EHG
Anatolia_N
WSHG
Russia_MA1_HG.SG
CHG
Russia_MLBA_Sintashta
Sweden_HG_Motala

0 Pakistan_Medieval_Udegram_Ghaznavid 1
1 ShahrISokhtaSubset 4
2 Kazakhstan_MLBA_OyDzhaylau 6
3 Alalakh_MLBA_outlier 1
4 Levant_BA 3
5 Cameroon_SMA.DG 1
6 Russia_Steppe_Eneolithic 3
7 ONG.SG 6
8 PPNB 11
9 Iran_GanjDareh_N 8
10 DevilsCave_N.SG 4
11 Russia_UstBelaya_Angara 11
12 EHG 3
13 Anatolia_N 30
14 WSHG 3
15 Russia_MA1_HG.SG 1
16 CHG 2
17 Russia_MLBA_Sintashta 19
18 Sweden_HG_Motala 6
jackknife block size: 0.050
snps: 1150513 indivs: 123
number of blocks for block jackknife: 714
## ncols: 1150513
coverage: Pakistan_Medieval_Udegram_Ghaznavid 613682
coverage: ShahrISokhtaSubset 841356
coverage: Kazakhstan_MLBA_OyDzhaylau 999558
coverage: Alalakh_MLBA_outlier 733730
coverage: Levant_BA 870086
coverage: Cameroon_SMA.DG 1140138
coverage: Russia_Steppe_Eneolithic 1008226
coverage: ONG.SG 1143397
coverage: PPNB 871625
coverage: Iran_GanjDareh_N 1057358
coverage: DevilsCave_N.SG 1149702
coverage: Russia_UstBelaya_Angara 1092594
coverage: EHG 1027057
coverage: Anatolia_N 1141220
coverage: WSHG 858019
coverage: Russia_MA1_HG.SG 805960
coverage: CHG 1149558
coverage: Russia_MLBA_Sintashta 1115156
coverage: Sweden_HG_Motala 1038843
Effective number of blocks: 621.675
numsnps used: 1150513
codimension 1
f4info:
f4rank: 3 dof: 10 chisq: 9.081 tail: 0.524420183 dofdiff: 12 chisqdiff: -9.081 taildiff: 1
B:
scale 1.000 1.000 1.000
Russia_Steppe_Eneolithic 1.141 0.315 0.709
ONG.SG -0.069 1.157 -0.545
PPNB 0.398 -2.057 -0.269
Iran_GanjDareh_N 0.024 0.350 2.830
DevilsCave_N.SG 0.138 1.028 0.004
Russia_UstBelaya_Angara 0.436 1.073 -0.198
EHG 1.612 0.387 -0.916
Anatolia_N 0.711 -1.791 -0.284
WSHG 1.465 0.999 0.159
Russia_MA1_HG.SG 0.925 0.682 0.051
CHG 0.488 -0.035 1.253
Russia_MLBA_Sintashta 1.480 -0.391 -0.460
Sweden_HG_Motala 1.670 -0.160 -1.161
A:
scale 690.949 926.907 2671.743
ShahrISokhtaSubset -1.046 0.967 -0.665
Kazakhstan_MLBA_OyDzhaylau 1.600 -0.142 -0.538
Alalakh_MLBA_outlier 0.200 -0.060 1.781
Levant_BA -0.554 -1.744 -0.310


full rank
f4info:
f4rank: 4 dof: 0 chisq: 0.000 tail: 1 dofdiff: 10 chisqdiff: 9.081 taildiff: 0.524420183
B:
scale 520.670 438.653 1509.354 447.656
Russia_Steppe_Eneolithic -0.991 0.998 0.849 -0.835
ONG.SG 0.663 -0.119 -0.797 -0.991
PPNB -1.532 0.533 -0.187 1.516
Iran_GanjDareh_N -0.260 -0.249 2.759 -0.500
DevilsCave_N.SG 0.159 -0.125 -0.716 -1.144
Russia_UstBelaya_Angara 0.121 0.311 -0.376 -1.178
EHG -0.992 1.719 -0.222 -0.883
Anatolia_N -1.663 0.815 -0.128 1.150
WSHG -0.910 1.238 0.012 -1.597
Russia_MA1_HG.SG -0.520 0.796 0.037 -1.042
CHG -0.564 0.425 1.731 -0.215
Russia_MLBA_Sintashta -1.452 1.529 0.010 -0.269
Sweden_HG_Motala -1.360 1.797 -0.528 -0.466
A:
scale 2.000 2.000 2.000 2.000
ShahrISokhtaSubset 2.000 0.000 0.000 0.000
Kazakhstan_MLBA_OyDzhaylau 0.000 2.000 0.000 0.000
Alalakh_MLBA_outlier 0.000 0.000 2.000 0.000
Levant_BA 0.000 0.000 0.000 2.000


best coefficients: 0.347 0.254 0.235 0.164
Jackknife mean: 0.347787428 0.254622772 0.233704917 0.163884884
std. errors: 0.050 0.031 0.076 0.032

error covariance (* 1,000,000)
2475 302 -3241 464
302 955 -1157 -99
-3241 -1157 5814 -1416
464 -99 -1416 1051


summ: Pakistan_Medieval_Udegram_Ghaznavid 4 0.524420 0.348 0.255 0.234 0.164 2475 302 -3241 464 955 ...
-1157 -99 5814 -1416 1051

fixed pat wt dof chisq tail prob
0000 0 10 9.081 0.52442 0.347 0.254 0.235 0.164
0001 1 11 198.240 0 -0.114 0.045 1.069 0.000 infeasible
0010 1 11 23.589 0.0145832 0.479 0.300 0.000 0.222
0100 1 11 62.246 3.53768e-09 0.196 0.000 0.655 0.149
1000 1 11 48.943 9.68444e-07 0.000 0.192 0.732 0.077
0011 2 12 85.532 3.59629e-13 0.579 0.421 0.000 0.000
0101 2 12 73.941 5.82284e-11 0.080 0.000 0.920 0.000
0110 2 12 133.463 1.24327e-22 0.637 0.000 0.000 0.363
1001 2 12 57.278 7.04133e-08 0.000 0.216 0.784 0.000
1010 2 12 323.658 0 0.000 0.531 0.000 0.469
1100 2 12 84.219 6.42941e-13 0.000 0.000 0.899 0.101
0111 3 13 307.752 0 1.000 0.000 0.000 0.000
1011 3 13 562.432 0 0.000 1.000 0.000 0.000
1101 3 13 76.122 5.88156e-11 0.000 0.000 1.000 0.000
1110 3 13 636.601 0 0.000 0.000 0.000 1.000
best pat: 0000 0.52442 - -
best pat: 0010 0.0145832 chi(nested): 14.508 p-value for nested model: 0.0001396
best pat: 1001 7.04133e-08 not nested
best pat: 1101 5.88156e-11 chi(nested): 18.844 p-value for nested model: 1.41883e-05

coeffs: 0.347 0.254 0.235 0.164

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

details: ShahrISokhtaSubset Russia_Steppe_Eneolithic -0.001902 -5.507816
details: Kazakhstan_MLBA_OyDzhaylau Russia_Steppe_Eneolithic 0.002275 7.013775
details: Alalakh_MLBA_outlier Russia_Steppe_Eneolithic 0.000563 1.490381
details: Levant_BA Russia_Steppe_Eneolithic -0.001865 -5.519242
dscore: Russia_Steppe_Eneolithic f4: -0.000255 Z: -0.864982

details: ShahrISokhtaSubset ONG.SG 0.001273 3.757871
details: Kazakhstan_MLBA_OyDzhaylau ONG.SG -0.000271 -0.853529
details: Alalakh_MLBA_outlier ONG.SG -0.000528 -1.420694
details: Levant_BA ONG.SG -0.002213 -6.833597
dscore: ONG.SG f4: -0.000113 Z: -0.392467

details: ShahrISokhtaSubset PPNB -0.002943 -8.414631
details: Kazakhstan_MLBA_OyDzhaylau PPNB 0.001215 3.715002
details: Alalakh_MLBA_outlier PPNB -0.000124 -0.320154
details: Levant_BA PPNB 0.003386 9.728007
dscore: PPNB f4: -0.000188 Z: -0.621043

details: ShahrISokhtaSubset Iran_GanjDareh_N -0.000500 -1.571595
details: Kazakhstan_MLBA_OyDzhaylau Iran_GanjDareh_N -0.000567 -1.901114
details: Alalakh_MLBA_outlier Iran_GanjDareh_N 0.001828 5.020231
details: Levant_BA Iran_GanjDareh_N -0.001117 -3.507134
dscore: Iran_GanjDareh_N f4: -0.000071 Z: -0.256933

details: ShahrISokhtaSubset DevilsCave_N.SG 0.000306 0.899993
details: Kazakhstan_MLBA_OyDzhaylau DevilsCave_N.SG -0.000285 -0.875879
details: Alalakh_MLBA_outlier DevilsCave_N.SG -0.000475 -1.301721
details: Levant_BA DevilsCave_N.SG -0.002556 -7.736192
dscore: DevilsCave_N.SG f4: -0.000496 Z: -1.695529

details: ShahrISokhtaSubset Russia_UstBelaya_Angara 0.000231 0.744884
details: Kazakhstan_MLBA_OyDzhaylau Russia_UstBelaya_Angara 0.000709 2.402924
details: Alalakh_MLBA_outlier Russia_UstBelaya_Angara -0.000249 -0.727779
details: Levant_BA Russia_UstBelaya_Angara -0.002631 -8.497344
dscore: Russia_UstBelaya_Angara f4: -0.000228 Z: -0.866418

details: ShahrISokhtaSubset EHG -0.001904 -5.302990
details: Kazakhstan_MLBA_OyDzhaylau EHG 0.003918 11.405673
details: Alalakh_MLBA_outlier EHG -0.000147 -0.356890
details: Levant_BA EHG -0.001973 -5.428512
dscore: EHG f4: -0.000022 Z: -0.070131

details: ShahrISokhtaSubset Anatolia_N -0.003195 -9.802161
details: Kazakhstan_MLBA_OyDzhaylau Anatolia_N 0.001858 6.164440
details: Alalakh_MLBA_outlier Anatolia_N -0.000085 -0.236733
details: Levant_BA Anatolia_N 0.002570 8.084175
dscore: Anatolia_N f4: -0.000236 Z: -0.858723

details: ShahrISokhtaSubset WSHG -0.001748 -4.276795
details: Kazakhstan_MLBA_OyDzhaylau WSHG 0.002821 7.417244
details: Alalakh_MLBA_outlier WSHG 0.000008 0.017260
details: Levant_BA WSHG -0.003568 -8.906077
dscore: WSHG f4: -0.000471 Z: -1.332582

details: ShahrISokhtaSubset Russia_MA1_HG.SG -0.000998 -2.625186
details: Kazakhstan_MLBA_OyDzhaylau Russia_MA1_HG.SG 0.001814 4.945375
details: Alalakh_MLBA_outlier Russia_MA1_HG.SG 0.000024 0.059011
details: Levant_BA Russia_MA1_HG.SG -0.002329 -6.219682
dscore: Russia_MA1_HG.SG f4: -0.000260 Z: -0.785746

details: ShahrISokhtaSubset CHG -0.001084 -3.213672
details: Kazakhstan_MLBA_OyDzhaylau CHG 0.000969 3.007423
details: Alalakh_MLBA_outlier CHG 0.001147 3.087752
details: Levant_BA CHG -0.000480 -1.431633
dscore: CHG f4: 0.000061 Z: 0.210226

details: ShahrISokhtaSubset Russia_MLBA_Sintashta -0.002788 -9.043499
details: Kazakhstan_MLBA_OyDzhaylau Russia_MLBA_Sintashta 0.003486 12.417777
details: Alalakh_MLBA_outlier Russia_MLBA_Sintashta 0.000007 0.020201
details: Levant_BA Russia_MLBA_Sintashta -0.000601 -2.006932
dscore: Russia_MLBA_Sintashta f4: -0.000178 Z: -0.684682

details: ShahrISokhtaSubset Sweden_HG_Motala -0.002611 -7.676428
details: Kazakhstan_MLBA_OyDzhaylau Sweden_HG_Motala 0.004097 13.152831
details: Alalakh_MLBA_outlier Sweden_HG_Motala -0.000350 -0.912400
details: Levant_BA Sweden_HG_Motala -0.001042 -3.106908
dscore: Sweden_HG_Motala f4: -0.000117 Z: -0.406573

[kpb]

That distance for me is kind of high, at least compared to the other two. I wonder why

[pegasus]

That distance for me is kind of high, at least compared to the other two. I wonder why

You have an extra CHG like affinity which has to be accounted for. Kamil has it too.

sample: :kpb
distance: 1.8566
Saidu_Sharif_H_o: 41.5
Gonur1_BA: 28
Srubnaya_Alakul_MLBA: 16
CG_IVCp: 12
Chokhopani_2700BP: 2.5

[Coldmountains]

Another interesting qpAdm , this is one of the Ghaznavids 7716, he surprisingly needed a Levantine source-based of the stats . On G25 looked similar to other Pashtuns but he is not typical at all of them ,given his excess Levantine-like ancestry,. His Y DNA is not Pashtun like at all either. Though his higher IVC ancestry ties him to the region, so my guess he was a warrior or a religious figure who had both local and foreign origins. The only vector to my mind which would have brought Levantine type ancestry would be via the Saffarids . He came out 25% Steppe related, 35% IVC related ,25% BMAC, 16% Caananite. Its a good working model, but more genomes would be needed to properly resolve this. The usual models failed miserably.

left pops:
Pakistan_Medieval_Udegram_Ghaznavid
ShahrISokhtaSubset
Kazakhstan_MLBA_OyDzhaylau
Alalakh_MLBA_outlier
Levant_BA

right pops:
Cameroon_SMA.DG
Russia_Steppe_Eneolithic
ONG.SG
PPNB
Iran_GanjDareh_N
DevilsCave_N.SG
Russia_UstBelaya_Angara
EHG
Anatolia_N
WSHG
Russia_MA1_HG.SG
CHG
Russia_MLBA_Sintashta
Sweden_HG_Motala

0 Pakistan_Medieval_Udegram_Ghaznavid 1
1 ShahrISokhtaSubset 4
2 Kazakhstan_MLBA_OyDzhaylau 6
3 Alalakh_MLBA_outlier 1
4 Levant_BA 3
5 Cameroon_SMA.DG 1
6 Russia_Steppe_Eneolithic 3
7 ONG.SG 6
8 PPNB 11
9 Iran_GanjDareh_N 8
10 DevilsCave_N.SG 4
11 Russia_UstBelaya_Angara 11
12 EHG 3
13 Anatolia_N 30
14 WSHG 3
15 Russia_MA1_HG.SG 1
16 CHG 2
17 Russia_MLBA_Sintashta 19
18 Sweden_HG_Motala 6
jackknife block size: 0.050
snps: 1150513 indivs: 123
number of blocks for block jackknife: 714
## ncols: 1150513
coverage: Pakistan_Medieval_Udegram_Ghaznavid 613682
coverage: ShahrISokhtaSubset 841356
coverage: Kazakhstan_MLBA_OyDzhaylau 999558
coverage: Alalakh_MLBA_outlier 733730
coverage: Levant_BA 870086
coverage: Cameroon_SMA.DG 1140138
coverage: Russia_Steppe_Eneolithic 1008226
coverage: ONG.SG 1143397
coverage: PPNB 871625
coverage: Iran_GanjDareh_N 1057358
coverage: DevilsCave_N.SG 1149702
coverage: Russia_UstBelaya_Angara 1092594
coverage: EHG 1027057
coverage: Anatolia_N 1141220
coverage: WSHG 858019
coverage: Russia_MA1_HG.SG 805960
coverage: CHG 1149558
coverage: Russia_MLBA_Sintashta 1115156
coverage: Sweden_HG_Motala 1038843
Effective number of blocks: 621.675
numsnps used: 1150513
codimension 1
f4info:
f4rank: 3 dof: 10 chisq: 9.081 tail: 0.524420183 dofdiff: 12 chisqdiff: -9.081 taildiff: 1
B:
scale 1.000 1.000 1.000
Russia_Steppe_Eneolithic 1.141 0.315 0.709
ONG.SG -0.069 1.157 -0.545
PPNB 0.398 -2.057 -0.269
Iran_GanjDareh_N 0.024 0.350 2.830
DevilsCave_N.SG 0.138 1.028 0.004
Russia_UstBelaya_Angara 0.436 1.073 -0.198
EHG 1.612 0.387 -0.916
Anatolia_N 0.711 -1.791 -0.284
WSHG 1.465 0.999 0.159
Russia_MA1_HG.SG 0.925 0.682 0.051
CHG 0.488 -0.035 1.253
Russia_MLBA_Sintashta 1.480 -0.391 -0.460
Sweden_HG_Motala 1.670 -0.160 -1.161
A:
scale 690.949 926.907 2671.743
ShahrISokhtaSubset -1.046 0.967 -0.665
Kazakhstan_MLBA_OyDzhaylau 1.600 -0.142 -0.538
Alalakh_MLBA_outlier 0.200 -0.060 1.781
Levant_BA -0.554 -1.744 -0.310


full rank
f4info:
f4rank: 4 dof: 0 chisq: 0.000 tail: 1 dofdiff: 10 chisqdiff: 9.081 taildiff: 0.524420183
B:
scale 520.670 438.653 1509.354 447.656
Russia_Steppe_Eneolithic -0.991 0.998 0.849 -0.835
ONG.SG 0.663 -0.119 -0.797 -0.991
PPNB -1.532 0.533 -0.187 1.516
Iran_GanjDareh_N -0.260 -0.249 2.759 -0.500
DevilsCave_N.SG 0.159 -0.125 -0.716 -1.144
Russia_UstBelaya_Angara 0.121 0.311 -0.376 -1.178
EHG -0.992 1.719 -0.222 -0.883
Anatolia_N -1.663 0.815 -0.128 1.150
WSHG -0.910 1.238 0.012 -1.597
Russia_MA1_HG.SG -0.520 0.796 0.037 -1.042
CHG -0.564 0.425 1.731 -0.215
Russia_MLBA_Sintashta -1.452 1.529 0.010 -0.269
Sweden_HG_Motala -1.360 1.797 -0.528 -0.466
A:
scale 2.000 2.000 2.000 2.000
ShahrISokhtaSubset 2.000 0.000 0.000 0.000
Kazakhstan_MLBA_OyDzhaylau 0.000 2.000 0.000 0.000
Alalakh_MLBA_outlier 0.000 0.000 2.000 0.000
Levant_BA 0.000 0.000 0.000 2.000


best coefficients: 0.347 0.254 0.235 0.164
Jackknife mean: 0.347787428 0.254622772 0.233704917 0.163884884
std. errors: 0.050 0.031 0.076 0.032

error covariance (* 1,000,000)
2475 302 -3241 464
302 955 -1157 -99
-3241 -1157 5814 -1416
464 -99 -1416 1051


summ: Pakistan_Medieval_Udegram_Ghaznavid 4 0.524420 0.348 0.255 0.234 0.164 2475 302 -3241 464 955 ...
-1157 -99 5814 -1416 1051

fixed pat wt dof chisq tail prob
0000 0 10 9.081 0.52442 0.347 0.254 0.235 0.164
0001 1 11 198.240 0 -0.114 0.045 1.069 0.000 infeasible
0010 1 11 23.589 0.0145832 0.479 0.300 0.000 0.222
0100 1 11 62.246 3.53768e-09 0.196 0.000 0.655 0.149
1000 1 11 48.943 9.68444e-07 0.000 0.192 0.732 0.077
0011 2 12 85.532 3.59629e-13 0.579 0.421 0.000 0.000
0101 2 12 73.941 5.82284e-11 0.080 0.000 0.920 0.000
0110 2 12 133.463 1.24327e-22 0.637 0.000 0.000 0.363
1001 2 12 57.278 7.04133e-08 0.000 0.216 0.784 0.000
1010 2 12 323.658 0 0.000 0.531 0.000 0.469
1100 2 12 84.219 6.42941e-13 0.000 0.000 0.899 0.101
0111 3 13 307.752 0 1.000 0.000 0.000 0.000
1011 3 13 562.432 0 0.000 1.000 0.000 0.000
1101 3 13 76.122 5.88156e-11 0.000 0.000 1.000 0.000
1110 3 13 636.601 0 0.000 0.000 0.000 1.000
best pat: 0000 0.52442 - -
best pat: 0010 0.0145832 chi(nested): 14.508 p-value for nested model: 0.0001396
best pat: 1001 7.04133e-08 not nested
best pat: 1101 5.88156e-11 chi(nested): 18.844 p-value for nested model: 1.41883e-05

coeffs: 0.347 0.254 0.235 0.164

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

details: ShahrISokhtaSubset Russia_Steppe_Eneolithic -0.001902 -5.507816
details: Kazakhstan_MLBA_OyDzhaylau Russia_Steppe_Eneolithic 0.002275 7.013775
details: Alalakh_MLBA_outlier Russia_Steppe_Eneolithic 0.000563 1.490381
details: Levant_BA Russia_Steppe_Eneolithic -0.001865 -5.519242
dscore: Russia_Steppe_Eneolithic f4: -0.000255 Z: -0.864982

details: ShahrISokhtaSubset ONG.SG 0.001273 3.757871
details: Kazakhstan_MLBA_OyDzhaylau ONG.SG -0.000271 -0.853529
details: Alalakh_MLBA_outlier ONG.SG -0.000528 -1.420694
details: Levant_BA ONG.SG -0.002213 -6.833597
dscore: ONG.SG f4: -0.000113 Z: -0.392467

details: ShahrISokhtaSubset PPNB -0.002943 -8.414631
details: Kazakhstan_MLBA_OyDzhaylau PPNB 0.001215 3.715002
details: Alalakh_MLBA_outlier PPNB -0.000124 -0.320154
details: Levant_BA PPNB 0.003386 9.728007
dscore: PPNB f4: -0.000188 Z: -0.621043

details: ShahrISokhtaSubset Iran_GanjDareh_N -0.000500 -1.571595
details: Kazakhstan_MLBA_OyDzhaylau Iran_GanjDareh_N -0.000567 -1.901114
details: Alalakh_MLBA_outlier Iran_GanjDareh_N 0.001828 5.020231
details: Levant_BA Iran_GanjDareh_N -0.001117 -3.507134
dscore: Iran_GanjDareh_N f4: -0.000071 Z: -0.256933

details: ShahrISokhtaSubset DevilsCave_N.SG 0.000306 0.899993
details: Kazakhstan_MLBA_OyDzhaylau DevilsCave_N.SG -0.000285 -0.875879
details: Alalakh_MLBA_outlier DevilsCave_N.SG -0.000475 -1.301721
details: Levant_BA DevilsCave_N.SG -0.002556 -7.736192
dscore: DevilsCave_N.SG f4: -0.000496 Z: -1.695529

details: ShahrISokhtaSubset Russia_UstBelaya_Angara 0.000231 0.744884
details: Kazakhstan_MLBA_OyDzhaylau Russia_UstBelaya_Angara 0.000709 2.402924
details: Alalakh_MLBA_outlier Russia_UstBelaya_Angara -0.000249 -0.727779
details: Levant_BA Russia_UstBelaya_Angara -0.002631 -8.497344
dscore: Russia_UstBelaya_Angara f4: -0.000228 Z: -0.866418

details: ShahrISokhtaSubset EHG -0.001904 -5.302990
details: Kazakhstan_MLBA_OyDzhaylau EHG 0.003918 11.405673
details: Alalakh_MLBA_outlier EHG -0.000147 -0.356890
details: Levant_BA EHG -0.001973 -5.428512
dscore: EHG f4: -0.000022 Z: -0.070131

details: ShahrISokhtaSubset Anatolia_N -0.003195 -9.802161
details: Kazakhstan_MLBA_OyDzhaylau Anatolia_N 0.001858 6.164440
details: Alalakh_MLBA_outlier Anatolia_N -0.000085 -0.236733
details: Levant_BA Anatolia_N 0.002570 8.084175
dscore: Anatolia_N f4: -0.000236 Z: -0.858723

details: ShahrISokhtaSubset WSHG -0.001748 -4.276795
details: Kazakhstan_MLBA_OyDzhaylau WSHG 0.002821 7.417244
details: Alalakh_MLBA_outlier WSHG 0.000008 0.017260
details: Levant_BA WSHG -0.003568 -8.906077
dscore: WSHG f4: -0.000471 Z: -1.332582

details: ShahrISokhtaSubset Russia_MA1_HG.SG -0.000998 -2.625186
details: Kazakhstan_MLBA_OyDzhaylau Russia_MA1_HG.SG 0.001814 4.945375
details: Alalakh_MLBA_outlier Russia_MA1_HG.SG 0.000024 0.059011
details: Levant_BA Russia_MA1_HG.SG -0.002329 -6.219682
dscore: Russia_MA1_HG.SG f4: -0.000260 Z: -0.785746

details: ShahrISokhtaSubset CHG -0.001084 -3.213672
details: Kazakhstan_MLBA_OyDzhaylau CHG 0.000969 3.007423
details: Alalakh_MLBA_outlier CHG 0.001147 3.087752
details: Levant_BA CHG -0.000480 -1.431633
dscore: CHG f4: 0.000061 Z: 0.210226

details: ShahrISokhtaSubset Russia_MLBA_Sintashta -0.002788 -9.043499
details: Kazakhstan_MLBA_OyDzhaylau Russia_MLBA_Sintashta 0.003486 12.417777
details: Alalakh_MLBA_outlier Russia_MLBA_Sintashta 0.000007 0.020201
details: Levant_BA Russia_MLBA_Sintashta -0.000601 -2.006932
dscore: Russia_MLBA_Sintashta f4: -0.000178 Z: -0.684682

details: ShahrISokhtaSubset Sweden_HG_Motala -0.002611 -7.676428
details: Kazakhstan_MLBA_OyDzhaylau Sweden_HG_Motala 0.004097 13.152831
details: Alalakh_MLBA_outlier Sweden_HG_Motala -0.000350 -0.912400
details: Levant_BA Sweden_HG_Motala -0.001042 -3.106908
dscore: Sweden_HG_Motala f4: -0.000117 Z: -0.406573

I would say you need to account for more "West-Asian"-shifted Proto-Pashtun ancestry from South Afghanistan + West Iranic geneflow starting to arrive from the achaemaenid period, which is more western shifted than BMAC or Shar-i-Sokhta ancestry. We dont have genomes from Iron Age Afghanistan to compare him with. Pashtuns from these region definetly have something more Seh_Gabi-shifted compared to Shar-i-Sokhta and BMAC. Compared to other Pashtun samples especially from Afghanistan these Udegram sample does not seem to pick more Levantine ancestry at least not more compared to other Afghan Pashtun samples when using Kandahari as reference for Proto-Pashtuns. Also his J2a-F3133>FGC9942>Y14698 Y-DNA was already found among ancient Karluk and Karakhanid samples from Central Asia so there is a good chance it is of local (BMAC?) origin. But it also could be from a "back" migration from Iran. This clade is definetly rare among modern day Pashtuns but we don't know if this was also true 1000 years ago.

Distance: 1.4885% / 0.01488517
Target: PAK_Udegram_MA_Ghaznavid:I7716
48.1 PAK_Udegram_IA
42.1 Pashtun_Kandahar
7.6 Saka_Tian_Shan_o
2.2 Levant_Hazor_MLBA

Distance: 1.3425% / 0.01342522
Target: Pashtun_Kabul_AVG
43.7 Pashtun_Kandahar
34.8 PAK_Udegram_IA
14.0 KAZ_Wusun
5.7 Levant_Megiddo_MLBA
1.8 Saka_Tian_Shan_o

Distance: 1.4491% / 0.01449136
Target: Pashtun_North_Afghanistan_AVG
56.1 Pashtun_Kandahar
28.2 PAK_Udegram_IA
10.3 Turk
5.4 Levant_Megiddo_MLBA

[pegasus]

I would say you need to account for more "West-Asian"-shifted Proto-Pashtun ancestry from South Afghanistan + West Iranic geneflow starting to arrive from the achaemaenid period, which is more western shifted than BMAC or Shar-i-Sokhta ancestry. We dont have genomes from Iron Age Afghanistan to compare him with. Pashtuns from these region definetly have something more Seh_Gabi-shifted compared to Shar-i-Sokhta and BMAC. Compared to other Pashtun samples especially from Afghanistan these Udegram sample does not seem to pick more Levantine ancestry at least not more compared to other Afghan Pashtun samples when using Kandahari as reference for Proto-Pashtuns. Also his J2a-F3133>FGC9942>Y14698 Y-DNA was already found among ancient Karluk and Karakhanid samples from Central Asia so there is a good chance it is of local (BMAC?) origin. But it also could be from a "back" migration from Iran. This clade is definetly rare among modern day Pashtuns but we don't know if this was also true 1000 years ago.

Distance: 1.4885% / 0.01488517
Target: PAK_Udegram_MA_Ghaznavid:I7716
48.1 PAK_Udegram_IA
42.1 Pashtun_Kandahar
7.6 Saka_Tian_Shan_o
2.2 Levant_Hazor_MLBA

Distance: 1.3425% / 0.01342522
Target: Pashtun_Kabul_AVG
43.7 Pashtun_Kandahar
34.8 PAK_Udegram_IA
14.0 KAZ_Wusun
5.7 Levant_Megiddo_MLBA
1.8 Saka_Tian_Shan_o

Distance: 1.4491% / 0.01449136
Target: Pashtun_North_Afghanistan_AVG
56.1 Pashtun_Kandahar
28.2 PAK_Udegram_IA
10.3 Turk
5.4 Levant_Megiddo_MLBA

Using Iran Chl or Hasanlu/Hajji Firuz IA alone failed surprisingly, he needed a distinctively Levantine source , Ebla or Levant BA, and a lot of it. Even if you look at the stats , he still needs a more Levantine source, not Iran more Syrian/Lebanese type ancestry. I guess there was more gene flow from Levant than I thought. Yes, Most Kandahar/Helmand Pashtuns definitely would have gotten further Plateau Iranian ancestry, along with Balochis, when it arrives is a good question. What was the subclade of the R1a for Ghaznavid 2959??