admixtools2 TUTORIAL for WINDOWS.

I would like to add that people can use plink files perfectly fine with admixtools2 on R-studio, one of the perks of the 2nd ed.

.bed would be the equivalent to .geno, .bim to .snp and .fam to .ind.

The process is exactly the same.

The only you thing you need is a code viewer like visualcodestudio, which I use, to read and edit the index .fam file.

I would like to publicly thank eupator for his service of turning my raw ftdna file into plink and merging it with Reich dataset. Thanks to that I have been able to run qpADM on my own autosomal data. Would highly recommend his service.

Some example runs I just ran:
56PkOES.png

xwzY629.png
 
Finally got a scientifically viable model for myself:
oJcG7Hl.png
p>0.05; se<0.05.
Had to read some academic paper on right tails to get to it though.

Model stands up for other populations, but the slavic proxy or the tail might need optimizing for some of them.
y9ig1Jw.png

^Middle Ages Doclea(Montenegro) samples, substantially Slavic per G25.
qx8lRrV.png

^Two of the most admixed 1800s Albanian samples from the Southern Arc. Middle Age samples and the other non-admixed moderns completely fail with any of the proxies. More or less in line with G25 models for these samples I would say, albeit on the lower side.

I really am looking forward to the Kuline samples from the Danubian Limes being published, hoping they are high quality samples, that can be used to model early Slavic component in the whole Balkans.
 
Can you give your right?

I want to try it on myself.

right = c("Ethiopia_4500BP", "China_Tianyuan", "Yoruba.DG", "Serbia_IronGates_Mesolithic","Lithuania_EMN_Narva ", "Turkey_Barcin_LN.SG", "Russia_Steppe_Eneolithic",
"Israel_C", "Iran_GanjDareh_N", "Russia_Samara_EBA_Yamnaya", "Turkey_Alalakh_MLBA", "Moldova_MBA_Catacomb",
"Greece_BA_Mycenaean", "Slovenia_EIA", "Netherlands_EIA","Bulgaria_EIA", "Russia_IA_Ingria.SG", "Sudan_EarlyChristian" , "Spain_Greek_oLocal")


So in reality, this is guided by the Cosmopolitanism at the Roman Danubian Frontier, Slavic Migrations, and the Genomic Formation of Modern Balkan Peoples papers tail.
7Z8pihI.png



The only additions I made in order to lower standard errors are the Moldovan Catacomb, the Lithuanian EMN, and Bulgaria_EIA. Which are in line with suggestion about improving right tails from Assessing the Performance of qpAdm: A Statistical Tool for Studying Population Admixture.

I could not find the documentation for the exact sample names they used, but I think the guesswork for stuff like Steppe_IA, Anatolia_N etc. should be good enough. Also Ethiopia 4500bp instead of West Africa Ancient, since I had no idea what that sample was referring to.

I wonder if it will work for you. For some of the Albanian samples in the HO dataset it did not work, and for some others it would work with minor tweaks to the Slavic proxy.
 
right = c("Ethiopia_4500BP", "China_Tianyuan", "Yoruba.DG", "Serbia_IronGates_Mesolithic","Lithuania_EMN_Narva ", "Turkey_Barcin_LN.SG", "Russia_Steppe_Eneolithic",
"Israel_C", "Iran_GanjDareh_N", "Russia_Samara_EBA_Yamnaya", "Turkey_Alalakh_MLBA", "Moldova_MBA_Catacomb",
"Greece_BA_Mycenaean", "Slovenia_EIA", "Netherlands_EIA","Bulgaria_EIA", "Russia_IA_Ingria.SG", "Sudan_EarlyChristian" , "Spain_Greek_oLocal")


It works for me as well, good job.

39% Empuries2 + 52.7% Armenia_LBA + 8.36% Slav invader. Tail is 5.39% and s.e. almost at 5%.

Code:
[COLOR=#06989A !important]Reading metadata...[/COLOR]
[COLOR=#06989A !important]ℹ Computing block lengths for 1150639 SNPs...[/COLOR]
[COLOR=#06989A !important]ℹ Computing 57 f4-statistics for block 713 out of 713...[/COLOR]
[COLOR=#06989A !important]ℹ "allsnps = TRUE" uses different SNPs for each f4-statistic[/COLOR]
.
.
.
[COLOR=#06989A !important]ℹ Computing admixture weights...[/COLOR]
[COLOR=#06989A !important]ℹ Computing standard errors...[/COLOR]
[COLOR=#06989A !important]ℹ Computing number of admixture waves...[/COLOR]
[COLOR=#C5060B]
[/COLOR][COLOR=#C5060B]warning: solve(): system is singular (rcond: 2.0141e-17); attempting approx solution
[/COLOR][COLOR=blue]> [/COLOR][COLOR=blue]results$weights
[/COLOR][COLOR=#949494 !important]# A tibble: 3 × 5[/COLOR]
  target left                       weight     se     z
  [COLOR=#949494 !important][I]<chr>[/I][/COLOR]  [COLOR=#949494 !important][I]<chr>[/I][/COLOR]                       [COLOR=#949494 !important][I]<dbl>[/I][/COLOR]  [COLOR=#949494 !important][I]<dbl>[/I][/COLOR] [COLOR=#949494 !important][I]<dbl>[/I][/COLOR]
[COLOR=#BCBCBC !important]1[/COLOR] dosas  Spain_Hellenistic_Emporion 0.390  0.063[U]6[/U]  6.12
[COLOR=#BCBCBC !important]2[/COLOR] dosas  Armenia_LBA.SG             0.527  0.073[U]9[/U]  7.13
[COLOR=#BCBCBC !important]3[/COLOR] dosas  AV2                        0.083[U]6[/U] 0.046[U]7[/U]  1.79
[COLOR=blue]> [/COLOR][COLOR=blue]results$popdrop
[/COLOR][COLOR=#949494 !important]# A tibble: 7 × 14[/COLOR]
  pat      wt   dof chisq        p f4rank Spain_Hellen…¹ Armen…²     AV2 feasi…³ best  dofdiff
  [COLOR=#949494 !important][I]<chr>[/I][/COLOR] [COLOR=#949494 !important][I]<dbl>[/I][/COLOR] [COLOR=#949494 !important][I]<dbl>[/I][/COLOR] [COLOR=#949494 !important][I]<dbl>[/I][/COLOR]    [COLOR=#949494 !important][I]<dbl>[/I][/COLOR]  [COLOR=#949494 !important][I]<dbl>[/I][/COLOR]          [COLOR=#949494 !important][I]<dbl>[/I][/COLOR]   [COLOR=#949494 !important][I]<dbl>[/I][/COLOR]   [COLOR=#949494 !important][I]<dbl>[/I][/COLOR] [COLOR=#949494 !important][I]<lgl>[/I][/COLOR]   [COLOR=#949494 !important][I]<lgl>[/I][/COLOR]   [COLOR=#949494 !important][I]<dbl>[/I][/COLOR]
[COLOR=#BCBCBC !important]1[/COLOR] 000       0    17  27.3 5.39[COLOR=#949494 !important]e[/COLOR][COLOR=#CC0000 !important]- 2[/COLOR]      2          0.390   0.527  0.083[U]6[/U] TRUE    [COLOR=#CC0000 !important]NA[/COLOR]         [COLOR=#CC0000 !important]NA[/COLOR]
 
right = c("Ethiopia_4500BP", "China_Tianyuan", "Yoruba.DG", "Serbia_IronGates_Mesolithic","Lithuania_EMN_Narva ", "Turkey_Barcin_LN.SG", "Russia_Steppe_Eneolithic",
"Israel_C", "Iran_GanjDareh_N", "Russia_Samara_EBA_Yamnaya", "Turkey_Alalakh_MLBA", "Moldova_MBA_Catacomb",
"Greece_BA_Mycenaean", "Slovenia_EIA", "Netherlands_EIA","Bulgaria_EIA", "Russia_IA_Ingria.SG", "Sudan_EarlyChristian" , "Spain_Greek_oLocal")


It works for me as well, good job.

39% Empuries2 + 52.7% Armenia_LBA + 8.36% Slav invader. Tail is 5.39% and s.e. almost at 5%.

Code:
Reading metadata...
ℹ Computing block lengths for 1150639 SNPs...
ℹ Computing 57 f4-statistics for block 713 out of 713...
ℹ "allsnps = TRUE" uses different SNPs for each f4-statistic
  Number of SNPs used for each f4-statistic:
.
.
.
ℹ Computing admixture weights...
ℹ Computing standard errors...
ℹ Computing number of admixture waves...

warning: solve(): system is singular (rcond: 2.0141e-17); attempting approx solution
> results$weights
# A tibble: 3 × 5
  target left                       weight     se     z
  <chr>  <chr>                       <dbl>  <dbl> <dbl>
1 dosas  Spain_Hellenistic_Emporion 0.390  0.0636  6.12
2 dosas  Armenia_LBA.SG             0.527  0.0739  7.13
3 dosas  AV2                        0.0836 0.0467  1.79
> results$popdrop
# A tibble: 7 × 14
  pat      wt   dof chisq        p f4rank Spain_Hellen…¹ Armen…²     AV2 feasi…³ best  dofdiff
  <chr> <dbl> <dbl> <dbl>    <dbl>  <dbl>          <dbl>   <dbl>   <dbl> <lgl>   <lgl>   <dbl>
1 000       0    17  27.3 5.39e- 2      2          0.390   0.527  0.0836 TRUE    NA         NA
 
It works for me as well, good job.

39% Empuries2 + 52.7% Armenia_LBA + 8.36% Slav invader. Tail is 5.39% and s.e. almost at 5%.

Code:
Reading metadata...
ℹ Computing block lengths for 1150639 SNPs...
ℹ Computing 57 f4-statistics for block 713 out of 713...
ℹ "allsnps = TRUE" uses different SNPs for each f4-statistic
  Number of SNPs used for each f4-statistic:
.
.
.
ℹ Computing admixture weights...
ℹ Computing standard errors...
ℹ Computing number of admixture waves...

warning: solve(): system is singular (rcond: 2.0141e-17); attempting approx solution
> results$weights
# A tibble: 3 × 5
  target left                       weight     se     z
  <chr>  <chr>                       <dbl>  <dbl> <dbl>
1 dosas  Spain_Hellenistic_Emporion 0.390  0.0636  6.12
2 dosas  Armenia_LBA.SG             0.527  0.0739  7.13
3 dosas  AV2                        0.0836 0.0467  1.79
> results$popdrop
# A tibble: 7 × 14
  pat      wt   dof chisq        p f4rank Spain_Hellen…¹ Armen…²     AV2 feasi…³ best  dofdiff
  <chr> <dbl> <dbl> <dbl>    <dbl>  <dbl>          <dbl>   <dbl>   <dbl> <lgl>   <lgl>   <dbl>
1 000       0    17  27.3 5.39e- 2      2          0.390   0.527  0.0836 TRUE    NA         NA

Wow, in your case its even more impressive, since for you it works even with 3 components!
 
Wow, in your case its even more impressive, since for you it works even with 3 components!


I compared the results of admixtools1 and admixtools2, using the same dataset, to check for inconsistencies between the two.

Here are the results (right list included in the admixtools1 output file below):

Admixtools1 on ubuntu wsl:

Code:
./qpAdm: parameter file: parqpadm.txt
### THE INPUT PARAMETERS
##PARAMETER NAME: VALUE
fstatsname: fstatsa.txt  
popleft: left.txt
popright: right.txt
details: YES
## qpAdm version: 1520
seed: 65374783
 *** recommended that inbreed be explicitly set ***
inbreed set NO

left pops:
Greek_2.DG
Turkey_N
CHG
Iran_N
EHG
Balkan_HG

right pops:
Mbuti.DG
Ethiopia_4500BP
Russia_MA1_HG.SG
Iberomaurusian
Natufian
Turkey_Epipaleolithic
Turkey_Boncuklu_N
Iran_Wezmeh_N.SG
SATP
Russia_Sidelkino_HG.SG
Bichon_WHG
ONG.SG

codimension 1
f4info: 
f4rank: 4 dof:      7 chisq:     9.244 tail:          0.235596564 dofdiff:      9 chisqdiff:    -9.244 taildiff:                    1
B:
          scale     1.000     1.000     1.000     1.000 
Ethiopia_4500BP    -0.029     0.105    -0.119    -0.380 
Russia_MA1_HG.SG     1.150    -0.818     1.269     0.115 
 Iberomaurusian     0.153     0.679     0.174     0.218 
       Natufian    -0.108     1.394     0.400     0.123 
Turkey_Epipaleolithic     0.071     1.838     0.712     0.655 
Turkey_Boncuklu_N    -0.044     1.743     0.786     0.950 
Iran_Wezmeh_N.SG    -0.661    -0.632    -0.646    -0.837 
           SATP    -0.316    -0.616    -0.529     2.903 
Russia_Sidelkino_HG.SG     1.910    -0.733     1.315     0.084 
     Bichon_WHG     2.314     0.389    -2.370    -0.555 
         ONG.SG     0.306    -0.179     0.124     0.048 
A:
          scale   226.311   370.811   663.176   798.022 
       Turkey_N     0.109     0.971     0.255    -0.064 
            CHG    -0.221    -1.151    -0.797     1.883 
         Iran_N    -0.595    -1.231    -0.449    -1.158 
            EHG     1.374    -1.031     1.596    -0.215 
      Balkan_HG     1.642     0.392    -1.245    -0.252 


full rank
f4info: 
f4rank: 5 dof:      0 chisq:     0.000 tail:                    1 dofdiff:      7 chisqdiff:     9.244 taildiff:          0.235596564
B:
          scale   381.550   252.795   212.991   139.921   129.761 
Ethiopia_4500BP     0.162    -0.207     0.112    -0.069     0.051 
Russia_MA1_HG.SG    -0.471     0.039    -0.365     1.712     0.630 
 Iberomaurusian     0.653    -0.548    -0.728    -0.114     0.154 
       Natufian     1.230    -1.227    -1.197    -0.572    -0.084 
Turkey_Epipaleolithic     1.839    -1.324    -1.759    -0.478     0.072 
Turkey_Boncuklu_N     1.898    -0.970    -1.611    -0.463    -0.014 
Iran_Wezmeh_N.SG    -0.825     0.377     1.144    -0.513    -0.530 
           SATP    -0.884     2.465    -0.268    -0.321    -0.396 
Russia_Sidelkino_HG.SG    -0.104    -0.149    -0.772     2.393     1.399 
     Bichon_WHG     0.533    -0.459    -1.086     1.046     2.853 
         ONG.SG    -0.265    -0.058    -0.211     0.311     0.173 
A:
          scale     2.236     2.236     2.236     2.236     2.236 
       Turkey_N     2.236     0.000     0.000     0.000     0.000 
            CHG     0.000     2.236     0.000     0.000     0.000 
         Iran_N     0.000     0.000     2.236     0.000     0.000 
            EHG     0.000     0.000     0.000     2.236     0.000 
      Balkan_HG     0.000     0.000     0.000     0.000     2.236 


best coefficients:     0.539     0.163     0.221     0.066     0.011 
totmean:      0.539     0.163     0.221     0.066     0.011 
boot mean:     0.539     0.163     0.221     0.066     0.011 
      std. errors:     0.022     0.034     0.032     0.024     0.023 

error covariance (* 1,000,000)
       473       -200       -143        130       -260 
      -200       1134       -831       -146         42 
      -143       -831       1013       -142        104 
       130       -146       -142        586       -427 
      -260         42        104       -427        541 


summ: Greek_2.DG    5      0.235597     0.539     0.163     0.221     0.066     0.011        473       -200       -143        130       -260   ...
      1134       -831       -146         42       1013   ...
      -142        104        586       -427        541 

    fixed pat  wt  dof     chisq       tail prob
        00000  0     7     9.244        0.235597     0.539     0.163     0.221     0.066     0.011 
        00001  1     8     9.159        0.329088     0.543     0.157     0.229     0.072     0.000 
        00010  1     8    17.593       0.0244951     0.526     0.178     0.239     0.000     0.057 
        00100  1     8    55.206     4.02551e-09     0.559     0.353     0.000     0.092    -0.004  infeasible
        01000  1     8    33.294     5.45153e-05     0.570     0.000     0.344     0.086     0.001 
        10000  1     8   340.443               0     0.000     1.341    -0.369    -0.211     0.238  infeasible
        00011  2     9    28.212     0.000879116     0.562     0.199     0.239     0.000     0.000 
        00101  2     9    55.354     1.04254e-08     0.561     0.357     0.000     0.082     0.000 
        00110  2     9    66.879     6.21065e-11     0.544     0.401     0.000     0.000     0.055 
        01001  2     9    32.339     0.000173962     0.573     0.000     0.338     0.089     0.000 
        01010  2     9    47.040     3.85798e-07     0.553     0.000     0.381     0.000     0.066 
        01100  2     9   296.715               0     0.806     0.000     0.000     0.299    -0.104  infeasible
        10001  2     9   427.673               0     0.000     3.143    -1.888    -0.254     0.000  infeasible
        10010  2     9   450.331               0     0.000     3.264    -2.130     0.000    -0.134  infeasible
        10100  2     9   363.070               0     0.000     0.909     0.000    -0.178     0.268  infeasible
        11000  2     9   607.471               0     0.000     0.000     0.790    -0.130     0.340  infeasible
        00111  3    10    78.741       8.858e-13     0.572     0.428     0.000     0.000     0.000 
        01011  3    10    60.202     3.31904e-09     0.601     0.000     0.399     0.000     0.000 
        01101  3    10   310.546               0     0.772     0.000     0.000     0.228     0.000 
        01110  3    10   457.237               0     0.866     0.000     0.000     0.000     0.134 
        10011  3    10   370.411               0     0.000     1.699    -0.699     0.000     0.000  infeasible
        10101  3    10   436.133               0     0.000     0.995     0.000     0.005     0.000 
        10110  3    10   388.990               0     0.000     0.848     0.000     0.000     0.152 
        11001  3    10   732.337               0     0.000     0.000     0.813     0.187     0.000 
        11010  3    10   619.180               0     0.000     0.000     0.750     0.000     0.250 
        11100  3    10  1274.261               0     0.000     0.000     0.000     3.339    -2.339  infeasible
        01111  4    11   527.691               0     1.000     0.000     0.000     0.000     0.000 
        10111  4    11   434.070               0     0.000     1.000     0.000     0.000     0.000 
        11011  4    11   797.385               0     0.000     0.000     1.000     0.000     0.000 
        11101  4    11  1608.061               0     0.000     0.000     0.000     1.000     0.000 
        11110  4    11  2254.461               0     0.000     0.000     0.000     0.000     1.000 
best pat:        00000         0.235597              -  -
best pat:        00001         0.329088  chi(nested):    -0.086 p-value for nested model:            -nan
best pat:        00011      0.000879116  chi(nested):    19.053 p-value for nested model:     1.27123e-05
best pat:        01011      3.31904e-09  chi(nested):    31.990 p-value for nested model:     1.54968e-08
best pat:        10111      3.52789e-86 not nested

coeffs:     0.539     0.163     0.221     0.066     0.011 

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

details:             Turkey_N      Ethiopia_4500BP     0.000424    1.519259
details:                  CHG      Ethiopia_4500BP    -0.000819   -1.943319
details:               Iran_N      Ethiopia_4500BP     0.000527    1.446609
details:                  EHG      Ethiopia_4500BP    -0.000491   -1.264315
details:            Balkan_HG      Ethiopia_4500BP     0.000396    1.249994
dscore:      Ethiopia_4500BP f4:     0.000183 Z:     0.664467

details:             Turkey_N     Russia_MA1_HG.SG    -0.001235   -2.712074
details:                  CHG     Russia_MA1_HG.SG     0.000155    0.231893
details:               Iran_N     Russia_MA1_HG.SG    -0.001716   -3.018083
details:                  EHG     Russia_MA1_HG.SG     0.012234   18.616298
details:            Balkan_HG     Russia_MA1_HG.SG     0.004857    8.876965
dscore:     Russia_MA1_HG.SG f4:    -0.000159 Z:    -0.351255

details:             Turkey_N       Iberomaurusian     0.001713    5.639241
details:                  CHG       Iberomaurusian    -0.002169   -4.825007
details:               Iran_N       Iberomaurusian    -0.003418   -8.445022
details:                  EHG       Iberomaurusian    -0.000815   -1.996934
details:            Balkan_HG       Iberomaurusian     0.001186    3.373016
dscore:       Iberomaurusian f4:    -0.000226 Z:    -0.731440

details:             Turkey_N             Natufian     0.003223    7.238133
details:                  CHG             Natufian    -0.004855   -7.541364
details:               Iran_N             Natufian    -0.005620  -10.149357
details:                  EHG             Natufian    -0.004088   -6.620905
details:            Balkan_HG             Natufian    -0.000649   -1.334749
dscore:             Natufian f4:    -0.000572 Z:    -1.334130

details:             Turkey_N Turkey_Epipaleolithic     0.004820   11.355981
details:                  CHG Turkey_Epipaleolithic    -0.005236   -8.213203
details:               Iran_N Turkey_Epipaleolithic    -0.008260  -14.836225
details:                  EHG Turkey_Epipaleolithic    -0.003419   -5.691162
details:            Balkan_HG Turkey_Epipaleolithic     0.000558    1.111311
dscore: Turkey_Epipaleolithic f4:    -0.000298 Z:    -0.704892

details:             Turkey_N    Turkey_Boncuklu_N     0.004975   15.007691
details:                  CHG    Turkey_Boncuklu_N    -0.003836   -8.146834
details:               Iran_N    Turkey_Boncuklu_N    -0.007564  -18.523965
details:                  EHG    Turkey_Boncuklu_N    -0.003307   -7.512148
details:            Balkan_HG    Turkey_Boncuklu_N    -0.000110   -0.291861
dscore:    Turkey_Boncuklu_N f4:     0.000168 Z:     0.523694

details:             Turkey_N     Iran_Wezmeh_N.SG    -0.002162   -5.121353
details:                  CHG     Iran_Wezmeh_N.SG     0.001489    2.514266
details:               Iran_N     Iran_Wezmeh_N.SG     0.005372   10.382691
details:                  EHG     Iran_Wezmeh_N.SG    -0.003667   -6.575823
details:            Balkan_HG     Iran_Wezmeh_N.SG    -0.004082   -8.745931
dscore:     Iran_Wezmeh_N.SG f4:    -0.000024 Z:    -0.057286

details:             Turkey_N                 SATP    -0.002316   -5.255131
details:                  CHG                 SATP     0.009753   13.619358
details:               Iran_N                 SATP    -0.001257   -2.274280
details:                  EHG                 SATP    -0.002291   -3.564509
details:            Balkan_HG                 SATP    -0.003048   -5.826569
dscore:                 SATP f4:    -0.000120 Z:    -0.276100

details:             Turkey_N Russia_Sidelkino_HG.SG    -0.000273   -0.632561
details:                  CHG Russia_Sidelkino_HG.SG    -0.000589   -0.962729
details:               Iran_N Russia_Sidelkino_HG.SG    -0.003623   -7.050157
details:                  EHG Russia_Sidelkino_HG.SG     0.017101   26.155016
details:            Balkan_HG Russia_Sidelkino_HG.SG     0.010778   20.692646
dscore: Russia_Sidelkino_HG.SG f4:     0.000204 Z:     0.484279

details:             Turkey_N           Bichon_WHG     0.001398    3.131017
details:                  CHG           Bichon_WHG    -0.001814   -2.779301
details:               Iran_N           Bichon_WHG    -0.005099   -9.532231
details:                  EHG           Bichon_WHG     0.007476   11.529451
details:            Balkan_HG           Bichon_WHG     0.021988   39.513454
dscore:           Bichon_WHG f4:     0.000065 Z:     0.147092

details:             Turkey_N               ONG.SG    -0.000693   -2.128153
details:                  CHG               ONG.SG    -0.000230   -0.498754
details:               Iran_N               ONG.SG    -0.000992   -2.397668
details:                  EHG               ONG.SG     0.002221    4.902100
details:            Balkan_HG               ONG.SG     0.001333    3.511750
dscore:               ONG.SG f4:    -0.000469 Z:    -1.454282

gendstat:             Mbuti.DG      Ethiopia_4500BP     0.664
gendstat:             Mbuti.DG     Russia_MA1_HG.SG    -0.351
gendstat:             Mbuti.DG       Iberomaurusian    -0.731
gendstat:             Mbuti.DG             Natufian    -1.334
gendstat:             Mbuti.DG Turkey_Epipaleolithic    -0.705
gendstat:             Mbuti.DG    Turkey_Boncuklu_N     0.524
gendstat:             Mbuti.DG     Iran_Wezmeh_N.SG    -0.057
gendstat:             Mbuti.DG                 SATP    -0.276
gendstat:             Mbuti.DG Russia_Sidelkino_HG.SG     0.484
gendstat:             Mbuti.DG           Bichon_WHG     0.147
gendstat:             Mbuti.DG               ONG.SG    -1.454
gendstat:      Ethiopia_4500BP     Russia_MA1_HG.SG    -0.683
gendstat:      Ethiopia_4500BP       Iberomaurusian    -1.098
gendstat:      Ethiopia_4500BP             Natufian    -1.587
gendstat:      Ethiopia_4500BP Turkey_Epipaleolithic    -0.993
gendstat:      Ethiopia_4500BP    Turkey_Boncuklu_N    -0.042
gendstat:      Ethiopia_4500BP     Iran_Wezmeh_N.SG    -0.449
gendstat:      Ethiopia_4500BP                 SATP    -0.619
gendstat:      Ethiopia_4500BP Russia_Sidelkino_HG.SG     0.042
gendstat:      Ethiopia_4500BP           Bichon_WHG    -0.238
gendstat:      Ethiopia_4500BP               ONG.SG    -1.622
gendstat:     Russia_MA1_HG.SG       Iberomaurusian    -0.135
gendstat:     Russia_MA1_HG.SG             Natufian    -0.733
gendstat:     Russia_MA1_HG.SG Turkey_Epipaleolithic    -0.258
gendstat:     Russia_MA1_HG.SG    Turkey_Boncuklu_N     0.713
gendstat:     Russia_MA1_HG.SG     Iran_Wezmeh_N.SG     0.261
gendstat:     Russia_MA1_HG.SG                 SATP     0.069
gendstat:     Russia_MA1_HG.SG Russia_Sidelkino_HG.SG     0.749
gendstat:     Russia_MA1_HG.SG           Bichon_WHG     0.423
gendstat:     Russia_MA1_HG.SG               ONG.SG    -0.661
gendstat:       Iberomaurusian             Natufian    -0.799
gendstat:       Iberomaurusian Turkey_Epipaleolithic    -0.157
gendstat:       Iberomaurusian    Turkey_Boncuklu_N     1.109
gendstat:       Iberomaurusian     Iran_Wezmeh_N.SG     0.458
gendstat:       Iberomaurusian                 SATP     0.219
gendstat:       Iberomaurusian Russia_Sidelkino_HG.SG     0.938
gendstat:       Iberomaurusian           Bichon_WHG     0.622
gendstat:       Iberomaurusian               ONG.SG    -0.598
gendstat:             Natufian Turkey_Epipaleolithic     0.538
gendstat:             Natufian    Turkey_Boncuklu_N     1.737
gendstat:             Natufian     Iran_Wezmeh_N.SG     1.052
gendstat:             Natufian                 SATP     0.826
gendstat:             Natufian Russia_Sidelkino_HG.SG     1.512
gendstat:             Natufian           Bichon_WHG     1.179
gendstat:             Natufian               ONG.SG     0.208
gendstat: Turkey_Epipaleolithic    Turkey_Boncuklu_N     1.209
gendstat: Turkey_Epipaleolithic     Iran_Wezmeh_N.SG     0.540
gendstat: Turkey_Epipaleolithic                 SATP     0.341
gendstat: Turkey_Epipaleolithic Russia_Sidelkino_HG.SG     1.023
gendstat: Turkey_Epipaleolithic           Bichon_WHG     0.705
gendstat: Turkey_Epipaleolithic               ONG.SG    -0.364
gendstat:    Turkey_Boncuklu_N     Iran_Wezmeh_N.SG    -0.452
gendstat:    Turkey_Boncuklu_N                 SATP    -0.640
gendstat:    Turkey_Boncuklu_N Russia_Sidelkino_HG.SG     0.089
gendstat:    Turkey_Boncuklu_N           Bichon_WHG    -0.244
gendstat:    Turkey_Boncuklu_N               ONG.SG    -1.720
gendstat:     Iran_Wezmeh_N.SG                 SATP    -0.192
gendstat:     Iran_Wezmeh_N.SG Russia_Sidelkino_HG.SG     0.454
gendstat:     Iran_Wezmeh_N.SG           Bichon_WHG     0.170
gendstat:     Iran_Wezmeh_N.SG               ONG.SG    -1.017
gendstat:                 SATP Russia_Sidelkino_HG.SG     0.616
gendstat:                 SATP           Bichon_WHG     0.342
gendstat:                 SATP               ONG.SG    -0.751
gendstat: Russia_Sidelkino_HG.SG           Bichon_WHG    -0.291
gendstat: Russia_Sidelkino_HG.SG               ONG.SG    -1.482
gendstat:           Bichon_WHG               ONG.SG    -1.135

##end of qpAdm:       39.980 seconds cpu        0.831 Mbytes in use


Admixtools2 on R-studio:

Code:
A tibble: 5 × 5
  target     left      weight     se      z
  <chr>      <chr>      <dbl>  <dbl>  <dbl>
1 Greek_2.DG Turkey_N  0.539  0.0219 24.6  
2 Greek_2.DG CHG       0.160  0.0350  4.56 
3 Greek_2.DG Iran_N    0.225  0.0325  6.92 
4 Greek_2.DG EHG       0.0622 0.0247  2.52 
5 Greek_2.DG Balkan_HG 0.0134 0.0234  0.572
> results$popdrop
# A tibble: 31 × 16
   pat      wt   dof  chisq        p f4rank Turkey_N    CHG Iran_N     EHG Balkan_HG feasible
   <chr> <dbl> <dbl>  <dbl>    <dbl>  <dbl>    <dbl>  <dbl>  <dbl>   <dbl>     <dbl> <lgl>   
 1 00000     0     7   8.16 3.19e- 1      4    0.539  0.160  0.225  0.0622   0.0134  TRUE    
 2 00001     1     8  18.6  1.74e- 2      3    0.545  0.159  0.227  0.0692  NA       TRUE    
 3 00010     1     8  22.3  4.46e- 3      3    0.528  0.169  0.248 NA        0.0552  TRUE    
 4 00100     1     8  99.4  5.58e-18      3    0.559  0.361 NA      0.0858  -0.00599 FALSE   
 5 01000     1     8  39.2  4.59e- 6      3    0.571 NA      0.344  0.0720   0.0127  TRUE    
 6 10000     1     8 379.   4.56e-77      3   NA      2.01  -0.895 -0.272    0.161   FALSE   
 7 00011     2     9  63.2  3.20e-10      2    0.561  0.185  0.254 NA       NA       TRUE    
 8 00101     2     9 162.   3.55e-30      2    0.536  0.400 NA      0.0646  NA       TRUE    
 9 00110     2     9 132.   4.18e-24      2    0.535  0.417 NA     NA        0.0483  TRUE    
10 01001     2     9  83.2  3.77e-14      2    0.574 NA      0.347  0.0790  NA       TRUE    
# … with 21 more rows, and 4 more variables: best <lgl>, dofdiff <dbl>, chisqdiff <dbl>,
#   p_nested <dbl>
# ℹ Use `print(n = ...)` to see more rows, and `colnames()` to see all variable names


As you can see, they are almost entirely identical.

So really, there's no really a point in choosing the one over the other, of course, admixtools2 being lightning fast in comparison.
 
I compared the results of admixtools1 and admixtools2, using the same dataset, to check for inconsistencies between the two.

Here are the results (right list included in the admixtools1 output file below):

Admixtools1 on ubuntu wsl:

Code:
./qpAdm: parameter file: parqpadm.txt
### THE INPUT PARAMETERS
##PARAMETER NAME: VALUE
fstatsname: fstatsa.txt  
popleft: left.txt
popright: right.txt
details: YES
## qpAdm version: 1520
seed: 65374783
 *** recommended that inbreed be explicitly set ***
inbreed set NO

left pops:
Greek_2.DG
Turkey_N
CHG
Iran_N
EHG
Balkan_HG

right pops:
Mbuti.DG
Ethiopia_4500BP
Russia_MA1_HG.SG
Iberomaurusian
Natufian
Turkey_Epipaleolithic
Turkey_Boncuklu_N
Iran_Wezmeh_N.SG
SATP
Russia_Sidelkino_HG.SG
Bichon_WHG
ONG.SG

codimension 1
f4info: 
f4rank: 4 dof:      7 chisq:     9.244 tail:          0.235596564 dofdiff:      9 chisqdiff:    -9.244 taildiff:                    1
B:
          scale     1.000     1.000     1.000     1.000 
Ethiopia_4500BP    -0.029     0.105    -0.119    -0.380 
Russia_MA1_HG.SG     1.150    -0.818     1.269     0.115 
 Iberomaurusian     0.153     0.679     0.174     0.218 
       Natufian    -0.108     1.394     0.400     0.123 
Turkey_Epipaleolithic     0.071     1.838     0.712     0.655 
Turkey_Boncuklu_N    -0.044     1.743     0.786     0.950 
Iran_Wezmeh_N.SG    -0.661    -0.632    -0.646    -0.837 
           SATP    -0.316    -0.616    -0.529     2.903 
Russia_Sidelkino_HG.SG     1.910    -0.733     1.315     0.084 
     Bichon_WHG     2.314     0.389    -2.370    -0.555 
         ONG.SG     0.306    -0.179     0.124     0.048 
A:
          scale   226.311   370.811   663.176   798.022 
       Turkey_N     0.109     0.971     0.255    -0.064 
            CHG    -0.221    -1.151    -0.797     1.883 
         Iran_N    -0.595    -1.231    -0.449    -1.158 
            EHG     1.374    -1.031     1.596    -0.215 
      Balkan_HG     1.642     0.392    -1.245    -0.252 


full rank
f4info: 
f4rank: 5 dof:      0 chisq:     0.000 tail:                    1 dofdiff:      7 chisqdiff:     9.244 taildiff:          0.235596564
B:
          scale   381.550   252.795   212.991   139.921   129.761 
Ethiopia_4500BP     0.162    -0.207     0.112    -0.069     0.051 
Russia_MA1_HG.SG    -0.471     0.039    -0.365     1.712     0.630 
 Iberomaurusian     0.653    -0.548    -0.728    -0.114     0.154 
       Natufian     1.230    -1.227    -1.197    -0.572    -0.084 
Turkey_Epipaleolithic     1.839    -1.324    -1.759    -0.478     0.072 
Turkey_Boncuklu_N     1.898    -0.970    -1.611    -0.463    -0.014 
Iran_Wezmeh_N.SG    -0.825     0.377     1.144    -0.513    -0.530 
           SATP    -0.884     2.465    -0.268    -0.321    -0.396 
Russia_Sidelkino_HG.SG    -0.104    -0.149    -0.772     2.393     1.399 
     Bichon_WHG     0.533    -0.459    -1.086     1.046     2.853 
         ONG.SG    -0.265    -0.058    -0.211     0.311     0.173 
A:
          scale     2.236     2.236     2.236     2.236     2.236 
       Turkey_N     2.236     0.000     0.000     0.000     0.000 
            CHG     0.000     2.236     0.000     0.000     0.000 
         Iran_N     0.000     0.000     2.236     0.000     0.000 
            EHG     0.000     0.000     0.000     2.236     0.000 
      Balkan_HG     0.000     0.000     0.000     0.000     2.236 


best coefficients:     0.539     0.163     0.221     0.066     0.011 
totmean:      0.539     0.163     0.221     0.066     0.011 
boot mean:     0.539     0.163     0.221     0.066     0.011 
      std. errors:     0.022     0.034     0.032     0.024     0.023 

error covariance (* 1,000,000)
       473       -200       -143        130       -260 
      -200       1134       -831       -146         42 
      -143       -831       1013       -142        104 
       130       -146       -142        586       -427 
      -260         42        104       -427        541 


summ: Greek_2.DG    5      0.235597     0.539     0.163     0.221     0.066     0.011        473       -200       -143        130       -260   ...
      1134       -831       -146         42       1013   ...
      -142        104        586       -427        541 

    fixed pat  wt  dof     chisq       tail prob
        00000  0     7     9.244        0.235597     0.539     0.163     0.221     0.066     0.011 
        00001  1     8     9.159        0.329088     0.543     0.157     0.229     0.072     0.000 
        00010  1     8    17.593       0.0244951     0.526     0.178     0.239     0.000     0.057 
        00100  1     8    55.206     4.02551e-09     0.559     0.353     0.000     0.092    -0.004  infeasible
        01000  1     8    33.294     5.45153e-05     0.570     0.000     0.344     0.086     0.001 
        10000  1     8   340.443               0     0.000     1.341    -0.369    -0.211     0.238  infeasible
        00011  2     9    28.212     0.000879116     0.562     0.199     0.239     0.000     0.000 
        00101  2     9    55.354     1.04254e-08     0.561     0.357     0.000     0.082     0.000 
        00110  2     9    66.879     6.21065e-11     0.544     0.401     0.000     0.000     0.055 
        01001  2     9    32.339     0.000173962     0.573     0.000     0.338     0.089     0.000 
        01010  2     9    47.040     3.85798e-07     0.553     0.000     0.381     0.000     0.066 
        01100  2     9   296.715               0     0.806     0.000     0.000     0.299    -0.104  infeasible
        10001  2     9   427.673               0     0.000     3.143    -1.888    -0.254     0.000  infeasible
        10010  2     9   450.331               0     0.000     3.264    -2.130     0.000    -0.134  infeasible
        10100  2     9   363.070               0     0.000     0.909     0.000    -0.178     0.268  infeasible
        11000  2     9   607.471               0     0.000     0.000     0.790    -0.130     0.340  infeasible
        00111  3    10    78.741       8.858e-13     0.572     0.428     0.000     0.000     0.000 
        01011  3    10    60.202     3.31904e-09     0.601     0.000     0.399     0.000     0.000 
        01101  3    10   310.546               0     0.772     0.000     0.000     0.228     0.000 
        01110  3    10   457.237               0     0.866     0.000     0.000     0.000     0.134 
        10011  3    10   370.411               0     0.000     1.699    -0.699     0.000     0.000  infeasible
        10101  3    10   436.133               0     0.000     0.995     0.000     0.005     0.000 
        10110  3    10   388.990               0     0.000     0.848     0.000     0.000     0.152 
        11001  3    10   732.337               0     0.000     0.000     0.813     0.187     0.000 
        11010  3    10   619.180               0     0.000     0.000     0.750     0.000     0.250 
        11100  3    10  1274.261               0     0.000     0.000     0.000     3.339    -2.339  infeasible
        01111  4    11   527.691               0     1.000     0.000     0.000     0.000     0.000 
        10111  4    11   434.070               0     0.000     1.000     0.000     0.000     0.000 
        11011  4    11   797.385               0     0.000     0.000     1.000     0.000     0.000 
        11101  4    11  1608.061               0     0.000     0.000     0.000     1.000     0.000 
        11110  4    11  2254.461               0     0.000     0.000     0.000     0.000     1.000 
best pat:        00000         0.235597              -  -
best pat:        00001         0.329088  chi(nested):    -0.086 p-value for nested model:            -nan
best pat:        00011      0.000879116  chi(nested):    19.053 p-value for nested model:     1.27123e-05
best pat:        01011      3.31904e-09  chi(nested):    31.990 p-value for nested model:     1.54968e-08
best pat:        10111      3.52789e-86 not nested

coeffs:     0.539     0.163     0.221     0.066     0.011 

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

details:             Turkey_N      Ethiopia_4500BP     0.000424    1.519259
details:                  CHG      Ethiopia_4500BP    -0.000819   -1.943319
details:               Iran_N      Ethiopia_4500BP     0.000527    1.446609
details:                  EHG      Ethiopia_4500BP    -0.000491   -1.264315
details:            Balkan_HG      Ethiopia_4500BP     0.000396    1.249994
dscore:      Ethiopia_4500BP f4:     0.000183 Z:     0.664467

details:             Turkey_N     Russia_MA1_HG.SG    -0.001235   -2.712074
details:                  CHG     Russia_MA1_HG.SG     0.000155    0.231893
details:               Iran_N     Russia_MA1_HG.SG    -0.001716   -3.018083
details:                  EHG     Russia_MA1_HG.SG     0.012234   18.616298
details:            Balkan_HG     Russia_MA1_HG.SG     0.004857    8.876965
dscore:     Russia_MA1_HG.SG f4:    -0.000159 Z:    -0.351255

details:             Turkey_N       Iberomaurusian     0.001713    5.639241
details:                  CHG       Iberomaurusian    -0.002169   -4.825007
details:               Iran_N       Iberomaurusian    -0.003418   -8.445022
details:                  EHG       Iberomaurusian    -0.000815   -1.996934
details:            Balkan_HG       Iberomaurusian     0.001186    3.373016
dscore:       Iberomaurusian f4:    -0.000226 Z:    -0.731440

details:             Turkey_N             Natufian     0.003223    7.238133
details:                  CHG             Natufian    -0.004855   -7.541364
details:               Iran_N             Natufian    -0.005620  -10.149357
details:                  EHG             Natufian    -0.004088   -6.620905
details:            Balkan_HG             Natufian    -0.000649   -1.334749
dscore:             Natufian f4:    -0.000572 Z:    -1.334130

details:             Turkey_N Turkey_Epipaleolithic     0.004820   11.355981
details:                  CHG Turkey_Epipaleolithic    -0.005236   -8.213203
details:               Iran_N Turkey_Epipaleolithic    -0.008260  -14.836225
details:                  EHG Turkey_Epipaleolithic    -0.003419   -5.691162
details:            Balkan_HG Turkey_Epipaleolithic     0.000558    1.111311
dscore: Turkey_Epipaleolithic f4:    -0.000298 Z:    -0.704892

details:             Turkey_N    Turkey_Boncuklu_N     0.004975   15.007691
details:                  CHG    Turkey_Boncuklu_N    -0.003836   -8.146834
details:               Iran_N    Turkey_Boncuklu_N    -0.007564  -18.523965
details:                  EHG    Turkey_Boncuklu_N    -0.003307   -7.512148
details:            Balkan_HG    Turkey_Boncuklu_N    -0.000110   -0.291861
dscore:    Turkey_Boncuklu_N f4:     0.000168 Z:     0.523694

details:             Turkey_N     Iran_Wezmeh_N.SG    -0.002162   -5.121353
details:                  CHG     Iran_Wezmeh_N.SG     0.001489    2.514266
details:               Iran_N     Iran_Wezmeh_N.SG     0.005372   10.382691
details:                  EHG     Iran_Wezmeh_N.SG    -0.003667   -6.575823
details:            Balkan_HG     Iran_Wezmeh_N.SG    -0.004082   -8.745931
dscore:     Iran_Wezmeh_N.SG f4:    -0.000024 Z:    -0.057286

details:             Turkey_N                 SATP    -0.002316   -5.255131
details:                  CHG                 SATP     0.009753   13.619358
details:               Iran_N                 SATP    -0.001257   -2.274280
details:                  EHG                 SATP    -0.002291   -3.564509
details:            Balkan_HG                 SATP    -0.003048   -5.826569
dscore:                 SATP f4:    -0.000120 Z:    -0.276100

details:             Turkey_N Russia_Sidelkino_HG.SG    -0.000273   -0.632561
details:                  CHG Russia_Sidelkino_HG.SG    -0.000589   -0.962729
details:               Iran_N Russia_Sidelkino_HG.SG    -0.003623   -7.050157
details:                  EHG Russia_Sidelkino_HG.SG     0.017101   26.155016
details:            Balkan_HG Russia_Sidelkino_HG.SG     0.010778   20.692646
dscore: Russia_Sidelkino_HG.SG f4:     0.000204 Z:     0.484279

details:             Turkey_N           Bichon_WHG     0.001398    3.131017
details:                  CHG           Bichon_WHG    -0.001814   -2.779301
details:               Iran_N           Bichon_WHG    -0.005099   -9.532231
details:                  EHG           Bichon_WHG     0.007476   11.529451
details:            Balkan_HG           Bichon_WHG     0.021988   39.513454
dscore:           Bichon_WHG f4:     0.000065 Z:     0.147092

details:             Turkey_N               ONG.SG    -0.000693   -2.128153
details:                  CHG               ONG.SG    -0.000230   -0.498754
details:               Iran_N               ONG.SG    -0.000992   -2.397668
details:                  EHG               ONG.SG     0.002221    4.902100
details:            Balkan_HG               ONG.SG     0.001333    3.511750
dscore:               ONG.SG f4:    -0.000469 Z:    -1.454282

gendstat:             Mbuti.DG      Ethiopia_4500BP     0.664
gendstat:             Mbuti.DG     Russia_MA1_HG.SG    -0.351
gendstat:             Mbuti.DG       Iberomaurusian    -0.731
gendstat:             Mbuti.DG             Natufian    -1.334
gendstat:             Mbuti.DG Turkey_Epipaleolithic    -0.705
gendstat:             Mbuti.DG    Turkey_Boncuklu_N     0.524
gendstat:             Mbuti.DG     Iran_Wezmeh_N.SG    -0.057
gendstat:             Mbuti.DG                 SATP    -0.276
gendstat:             Mbuti.DG Russia_Sidelkino_HG.SG     0.484
gendstat:             Mbuti.DG           Bichon_WHG     0.147
gendstat:             Mbuti.DG               ONG.SG    -1.454
gendstat:      Ethiopia_4500BP     Russia_MA1_HG.SG    -0.683
gendstat:      Ethiopia_4500BP       Iberomaurusian    -1.098
gendstat:      Ethiopia_4500BP             Natufian    -1.587
gendstat:      Ethiopia_4500BP Turkey_Epipaleolithic    -0.993
gendstat:      Ethiopia_4500BP    Turkey_Boncuklu_N    -0.042
gendstat:      Ethiopia_4500BP     Iran_Wezmeh_N.SG    -0.449
gendstat:      Ethiopia_4500BP                 SATP    -0.619
gendstat:      Ethiopia_4500BP Russia_Sidelkino_HG.SG     0.042
gendstat:      Ethiopia_4500BP           Bichon_WHG    -0.238
gendstat:      Ethiopia_4500BP               ONG.SG    -1.622
gendstat:     Russia_MA1_HG.SG       Iberomaurusian    -0.135
gendstat:     Russia_MA1_HG.SG             Natufian    -0.733
gendstat:     Russia_MA1_HG.SG Turkey_Epipaleolithic    -0.258
gendstat:     Russia_MA1_HG.SG    Turkey_Boncuklu_N     0.713
gendstat:     Russia_MA1_HG.SG     Iran_Wezmeh_N.SG     0.261
gendstat:     Russia_MA1_HG.SG                 SATP     0.069
gendstat:     Russia_MA1_HG.SG Russia_Sidelkino_HG.SG     0.749
gendstat:     Russia_MA1_HG.SG           Bichon_WHG     0.423
gendstat:     Russia_MA1_HG.SG               ONG.SG    -0.661
gendstat:       Iberomaurusian             Natufian    -0.799
gendstat:       Iberomaurusian Turkey_Epipaleolithic    -0.157
gendstat:       Iberomaurusian    Turkey_Boncuklu_N     1.109
gendstat:       Iberomaurusian     Iran_Wezmeh_N.SG     0.458
gendstat:       Iberomaurusian                 SATP     0.219
gendstat:       Iberomaurusian Russia_Sidelkino_HG.SG     0.938
gendstat:       Iberomaurusian           Bichon_WHG     0.622
gendstat:       Iberomaurusian               ONG.SG    -0.598
gendstat:             Natufian Turkey_Epipaleolithic     0.538
gendstat:             Natufian    Turkey_Boncuklu_N     1.737
gendstat:             Natufian     Iran_Wezmeh_N.SG     1.052
gendstat:             Natufian                 SATP     0.826
gendstat:             Natufian Russia_Sidelkino_HG.SG     1.512
gendstat:             Natufian           Bichon_WHG     1.179
gendstat:             Natufian               ONG.SG     0.208
gendstat: Turkey_Epipaleolithic    Turkey_Boncuklu_N     1.209
gendstat: Turkey_Epipaleolithic     Iran_Wezmeh_N.SG     0.540
gendstat: Turkey_Epipaleolithic                 SATP     0.341
gendstat: Turkey_Epipaleolithic Russia_Sidelkino_HG.SG     1.023
gendstat: Turkey_Epipaleolithic           Bichon_WHG     0.705
gendstat: Turkey_Epipaleolithic               ONG.SG    -0.364
gendstat:    Turkey_Boncuklu_N     Iran_Wezmeh_N.SG    -0.452
gendstat:    Turkey_Boncuklu_N                 SATP    -0.640
gendstat:    Turkey_Boncuklu_N Russia_Sidelkino_HG.SG     0.089
gendstat:    Turkey_Boncuklu_N           Bichon_WHG    -0.244
gendstat:    Turkey_Boncuklu_N               ONG.SG    -1.720
gendstat:     Iran_Wezmeh_N.SG                 SATP    -0.192
gendstat:     Iran_Wezmeh_N.SG Russia_Sidelkino_HG.SG     0.454
gendstat:     Iran_Wezmeh_N.SG           Bichon_WHG     0.170
gendstat:     Iran_Wezmeh_N.SG               ONG.SG    -1.017
gendstat:                 SATP Russia_Sidelkino_HG.SG     0.616
gendstat:                 SATP           Bichon_WHG     0.342
gendstat:                 SATP               ONG.SG    -0.751
gendstat: Russia_Sidelkino_HG.SG           Bichon_WHG    -0.291
gendstat: Russia_Sidelkino_HG.SG               ONG.SG    -1.482
gendstat:           Bichon_WHG               ONG.SG    -1.135

##end of qpAdm:       39.980 seconds cpu        0.831 Mbytes in use


Admixtools2 on R-studio:

Code:
A tibble: 5 × 5
  target     left      weight     se      z
  <chr>      <chr>      <dbl>  <dbl>  <dbl>
1 Greek_2.DG Turkey_N  0.539  0.0219 24.6  
2 Greek_2.DG CHG       0.160  0.0350  4.56 
3 Greek_2.DG Iran_N    0.225  0.0325  6.92 
4 Greek_2.DG EHG       0.0622 0.0247  2.52 
5 Greek_2.DG Balkan_HG 0.0134 0.0234  0.572
> results$popdrop
# A tibble: 31 × 16
   pat      wt   dof  chisq        p f4rank Turkey_N    CHG Iran_N     EHG Balkan_HG feasible
   <chr> <dbl> <dbl>  <dbl>    <dbl>  <dbl>    <dbl>  <dbl>  <dbl>   <dbl>     <dbl> <lgl>   
 1 00000     0     7   8.16 3.19e- 1      4    0.539  0.160  0.225  0.0622   0.0134  TRUE    
 2 00001     1     8  18.6  1.74e- 2      3    0.545  0.159  0.227  0.0692  NA       TRUE    
 3 00010     1     8  22.3  4.46e- 3      3    0.528  0.169  0.248 NA        0.0552  TRUE    
 4 00100     1     8  99.4  5.58e-18      3    0.559  0.361 NA      0.0858  -0.00599 FALSE   
 5 01000     1     8  39.2  4.59e- 6      3    0.571 NA      0.344  0.0720   0.0127  TRUE    
 6 10000     1     8 379.   4.56e-77      3   NA      2.01  -0.895 -0.272    0.161   FALSE   
 7 00011     2     9  63.2  3.20e-10      2    0.561  0.185  0.254 NA       NA       TRUE    
 8 00101     2     9 162.   3.55e-30      2    0.536  0.400 NA      0.0646  NA       TRUE    
 9 00110     2     9 132.   4.18e-24      2    0.535  0.417 NA     NA        0.0483  TRUE    
10 01001     2     9  83.2  3.77e-14      2    0.574 NA      0.347  0.0790  NA       TRUE    
# … with 21 more rows, and 4 more variables: best <lgl>, dofdiff <dbl>, chisqdiff <dbl>,
#   p_nested <dbl>
# ℹ Use `print(n = ...)` to see more rows, and `colnames()` to see all variable names


As you can see, they are almost entirely identical.

So really, there's no really a point in choosing the one over the other, of course, admixtools2 being lightning fast in comparison.

Interesting.

Could you check this?

https://anthrogenica.com/showthread.php?26726-QPADM-runs&p=919453&viewfull=1#post919453

Am I misunderstanding, that in one of the runs there the model failed while in the other it passed? All material to replicate including the modified ind is there.

I have had multiple people message me, and seen myself that admixtools2 can give vastly different results(orders of magniute) for the same run, run different times. I still can get some models to be replicable most of the time, while others are really random, whether its the tail, or some mistakes me and 2-3 other fellas that I have been in contact with are doing, I am not quite sure.
 
There's probably a mistake in the .ind file somewhere in there, misnomer or something like that.

If you can be bothered, give me the right/left lists with the original naming and I will run them on my machine.
 
list:

West_Africa_ancient


Sudan_EarlyChristian


EHG


Iron_Gates_HG


Levant_N


Anatolia_N


Iran_Neolithic


Yamnaya_Samara


Alalakh_MLBA


Iberia_IA


Mycenaean


Slovenia_EIA


Netherlands_IA


Russia_Ingria_IA


Steppe_IA


Albanian.HO


Albania_BA_IA


Slavic

---
Last three are the left, the others are the right.
You have the ind pastebin. I made sure to use the same ind file for both runs so I doubt that is the reason. But lets see.
 
I would give you the original naming of the tail/samples but its a very synthetic list, made using supplements from Danubian Limes paper. Doubt anyone would wanna go through the pain of manually renaming some 200 samples. But using the same ind on both admix1 and admix2 would eliminate the ind as the point of failure I think. As long as both results are the same.
 
I don't understand the name, which HG is EHG for example.

Also, you might want to look at this:

https://uqrmaie1.github.io/admixtoo...results-between-admixtools-and-admixtools-2-1

That is just the thing I was looking for thanks!

About the HG question, I was replicating this https://www.biorxiv.org/content/10.1101/2021.08.30.458211v1.supplementary-material. But trust me too much of a pain manually repeating what I did.

Btw, you were not kidding when you said

It's not a big deal, messing around with plink with the inconsistencies errors is more ball busting.

Like holy... that is a headache.
I went the VCF route and no idea if it worked. :embarassed:
 
eupator said:
Russki said:
Hello. Can you help me know what my_f2_dir means?




_C5Y9XhK7nI.jpg







I downloaded David Reich files and there is no my_f2_dir there, they look like this:




ujJtwvRrr1w.jpg
The f2_dir hosts files that are generated by your f2 calculations, you just need to name it and it will be auto-created.




How to make f2 calculations to generate f2_dir hosts files?


I'm following your instruction step-by-step and I'm at the point where I have a ready software and 2 datasets of reichdata


If you see (based on these screenshots below) that I did something wrong until this point, please tell me




Zq-y6C3cuc0.jpg



YOcIYS345Nc.jpg



LSM69DFKQ-Q.jpg



ujJtwvRrr1w.jpg
 
So far so good,

1240K are the high-SNP files and the HO are the low-SNP but with the moderns in from the Human Origin database.
 

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