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Thread: Deep Ancestry using qpAdm

  1. #1
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    Lightbulb Deep Ancestry using qpAdm

    This thread is for posting the qpAdm results for our Iranian members, and subsequent discussion. As previously mentioned, fits with chisq values over 2 and tail probabilities less than 80% should not be taken too seriously.

    I have purposely kept the left pops and right pops the same for all members, so that the fixed path values (100% modeling) between the various members can be kept comparable. Although some members may not have gotten good fits, their fixed path values are nonetheless informative, and I may attempt a qpAdm based PCA and dendogram, as I believed I have figured out a way to do that. This would be a first as far as I am aware, and it would be interesting to compare the clustering based on it, to the usual ADMIXTURE based PCAs out there (recent ancestry). We may be able to get clustering on a more ancestral level doing so.

    A general comment on results obtained using formal methods. I have noticed that some members get uptight (directed at non-Iranian members) when analysis based on formal methods reveals results/ancestry that does not conform to their preconceived ideas/beliefs, or ADMIXTURE, which is based on recent drift. Those members should remember that their written records only go back a few hundred years at best, and that the further back we go in time, the higher the probability that some of your ancestry will deviate from the average ancestry of your ethnic group. This happens for reasons such as voluntary integration of individuals from one ethnic group into another, or forced integration.

    I will circle around and re-run the Pashtun members using the same exact base pops used for Kurds and Iranian members under this thread. I will then move on to the other project members. Once I have done almost everyone, I will work on the PCA and dendogram. It will take me a little while to get to everyone, as I do this on a time-permitting, non paid voluntary basis.

    Down the road, I hope to start modeling members using some of the newly sequenced genomes, which I incorporated into my dataset when they first came out, but have not had the time to analyze.

    From our Iranian members, Jesus was the only one who obtained excellent fits using my base populations. Thus his results are the most realistic.

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  3. #2
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    NO SAMPLE Andronovo2 Scythian_IA Chechen Saudi Mongola CHISQ TAIL PROBABILITY
    1 JESUS 0% 0% 30% 70% 0% 0.208 99%
    2 JESUS 0% 5% 22% 73% 0% 0.159 98%
    3 JESUS 0% 16% 0% 84% 0% 0.464 98%
    4 JESUS 0% 0% 30% 70% 0% 0.206 98%
    5 JESUS 0% 0% 0% 100% 0% 4.851 43%
    6 JESUS 0% 0% 100% 0% 0% 24.936 0%
    7 JESUS 100% 0% 0% 0% 0% 30.541 0%
    8 JESUS 0% 100% 0% 0% 0% 57.245 0%
    9 JESUS 0% 0% 0% 0% 100% 1208.666 0%


    0 .Jesus 1
    1 Andronovo2 1
    2 Scythian_IA 1
    3 Chechen 9
    4 Saudi 8
    5 Mongola 6
    6 MbutiPygmy 10
    7 Karitiana 12
    8 Onge 9
    9 Han 33
    10 Yoruba 70
    11 Ami 10
    jackknife block size: 0.05
    snps: 529924 indivs: 170
    number of blocks for block jackknife: 711
    dof (jackknife): 616.942
    numsnps used: 26176
    codimension 1
    f4info:
    f4rank: 4 dof: 1 chisq: 0.016 tail: 0.898991679 dofdiff: 3 chisqdiff: -0.016 taildiff:
    B:
    scale 1 1 1 1
    Karitiana 1.002 1.766 0.52 -0.25
    Onge 0.706 0.667 -1.36 0.478
    Han 1.348 -0.868 -0.548 1.001
    Yoruba 0.006 0.133 1.361 1.63
    Ami 1.297 -0.816 0.853 -1.025
    A:
    scale 111.939 1129.126 6322.085 17384.372
    Andronovo2 0.459 1.591 -1.17 1.094
    Scythian_IA 0.7 1.033 1.753 0.353
    Chechen 0.292 0.774 -0.6 -1.659
    Saudi -0.134 -0.313 -0.255 0.935
    Mongola 2.048 -0.839 -0.365 0.231


    full rank 1
    f4info:
    f4rank: 5 dof: 0 chisq: 0 tail: 1 dofdiff: 1 chisqdiff: 0.016 taildiff:
    B:
    scale 1 1 1 1 1
    Karitiana 1.003 1.77 0.55 -0.308 -0.681
    Onge 0.704 0.651 -1.361 0.483 1.412
    Han 1.35 -0.861 -0.523 0.966 -1.109
    Yoruba 0.005 0.125 1.358 1.633 0.69
    Ami 1.295 -0.828 0.854 -1.036 0.914
    A:
    scale 112.143 1129.243 6301.212 17638.148 69206.007
    Andronovo2 0.458 1.592 -1.121 0.983 0.183
    Scythian_IA 0.699 1.034 1.823 0.138 -0.32
    Chechen 0.289 0.773 -0.54 -1.861 -0.751
    Saudi -0.138 -0.313 -0.19 0.74 -2.073
    Mongola 2.049 -0.838 -0.307 0.046 0.035


    best coefficients: -0.12 0.128 0.33 0.681 -0.019
    ssres:
    -0.000005107 -0.000076991 -0.000030378 -0.000022618 -0.000040885
    -0.119976156 -1.808709321 -0.713659886 -0.531344713 -0.96048877

    Jackknife mean: -0.053726673 0.110256633 0.243996791 0.712588779 -0.01311553
    std. errors: 0.435 0.377 0.797 0.295 0.062

    error covariance (* 1000000)
    189406 -10920 -275434 88743 8204
    -10920 141952 -149318 36936 -18650
    -275434 -149318 634913 -214616 4455
    88743 36936 -214616 86732 2205
    8204 -18650 4455 2205 3786


    fixed pat wt dof chisq tail prob
    0 0 1 0.016 0 -0.12 0.128 0.33 0.681 -0.019 infeasible
    1 1 2 0.119 0 -0.081 0.033 0.357 0.691 0 infeasible
    10 1 2 1.579 0 -0.081 0.033 0.357 0.691 0 infeasible
    100 1 2 0.184 0 0.017 0.212 0 0.793 -0.023 infeasible
    1000 1 2 0.135 0 -0.114 0 0.472 0.645 -0.003 infeasible
    10000 1 2 0.096 0 0 0.123 0.153 0.738 -0.014 infeasible
    11 2 3 1.708 0 -1.164 -0.339 2.503 0 0 infeasible
    101 2 3 0.322 0.955875 0.079 0.106 0 0.815 0
    110 2 3 3.453 0 -6.75 9.208 0 0 -1.458 infeasible
    1001 2 3 0.141 0 -0.101 0 0.441 0.659 0 infeasible
    1010 2 3 1.579 0 -1.273 0 2.331 0 -0.058 infeasible
    1100 2 3 0.59 0.898616 0.171 0 0 0.817 0.012
    10001 2 3 0.159 0.983921 0 0.046 0.223 0.73 0
    10010 2 3 3.858 0 0 -1.939 2.704 0 0.235 infeasible
    10100 2 3 0.188 0 0 0.231 0 0.794 -0.025 infeasible
    11000 2 3 0.206 0.976586 0 0 0.298 0.7 0.001
    111 3 4 9.131 0 3.011 -2.011 0 0 0 infeasible
    1011 3 4 2.405 0 3.011 -2.011 0 0 0 infeasible
    1101 3 4 0.743 0.945895 0.204 0 0 0.796 0
    1110 3 4 20.71 0 1.129 0 0 0 -0.129 infeasible
    10011 3 4 6.576 0 0 -0.718 1.718 0 0 infeasible
    10101 3 4 0.464 0.97695 0 0.159 0 0.841 0
    10110 3 4 13.526 0 0 1.328 0 0 -0.328 infeasible
    11001 3 4 0.208 0.99496 0 0 0.304 0.696 0
    11010 3 4 14.438 0 0 0 1.083 0 -0.083 infeasible
    11100 3 4 2.347 0.672234 0 0 0 0.963 0.037
    1111 4 5 30.541 1.15E-05 1 0 0 0 0
    10111 4 5 57.245 4.50E-11 0 1 0 0 0
    11011 4 5 24.936 0.000143372 0 0 1 0 0
    11101 4 5 4.851 0.434337 0 0 0 1 0
    11110 4 5 1208.666 0 0 0 0 0 1
    best pat: 0 0 - -
    best pat: 1 0 chi(nested): 0.103 p-value for nested model: 0.747916
    best pat: 10001 0.983921 chi(nested): 0.04 p-value for nested model: 0.842287
    best pat: 11001 0.99496 chi(nested): 0.049 p-value for nested model: 0.825066
    best pat: 11101 0.434337 chi(nested): 4.643 p-value for nested model: 0.0311782

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  5. #3
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    NO SAMPLE Andronovo2 Scythian_IA Chechen Saudi Mongola CHISQ TAIL PROBABILITY
    1 NK19191 49% 0% 0% 46% 5% 3.949 27%
    2 NK19191 67% 0% 0% 34% 0% 5.843 21%
    3 NK19191 0% 0% 100% 0% 0% 8.575 13%
    4 NK19191 100% 0% 0% 0% 0% 11.106 5%
    5 NK19191 0% 100% 0% 0% 0% 34.994 0%
    6 NK19191 0% 0% 0% 100% 0% 57.635 0%
    7 NK19191 0% 0% 0% 0% 100% 1118.337 0%

    0 .NK19191 1
    1 Andronovo2 1
    2 Scythian_IA 1
    3 Chechen 9
    4 Saudi 8
    5 Mongola 6
    6 MbutiPygmy 10
    7 Karitiana 12
    8 Onge 9
    9 Han 33
    10 Yoruba 70
    11 Ami 10
    jackknife block size: 0.05
    snps: 502652 indivs: 170
    number of blocks for block jackknife: 711
    dof (jackknife): 617.461
    numsnps used: 26209
    codimension 1
    f4info:
    f4rank: 4 dof: 1 chisq: 0.308 tail: 0.578656933 dofdiff: 3 chisqdiff: -0.308 taildiff:
    B:
    scale 1 1 1 1
    Karitiana 0.96 1.89 0.254 -0.533
    Onge 0.622 0.278 -1.797 0.345
    Han 1.37 -0.91 -0.04 0.352
    Yoruba 0.035 0.419 1.014 1.938
    Ami 1.347 -0.588 0.821 -0.846
    A:
    scale 128.859 1330.23 2541.876 13720.147
    Andronovo2 0.274 1.455 -0.271 1.458
    Scythian_IA 0.549 1.198 1.111 0.546
    Chechen 0.076 0.551 0.714 -1.415
    Saudi -0.409 -0.824 1.783 0.684
    Mongola 2.11 -0.682 0.024 0.324


    full rank 1
    f4info:
    f4rank: 5 dof: 0 chisq: 0 tail: 1 dofdiff: 1 chisqdiff: 0.308 taildiff:
    B:
    scale 1 1 1 1 1
    Karitiana 0.961 1.911 -0.25 -0.528 -0.284
    Onge 0.616 0.246 1.893 0.817 0.557
    Han 1.374 -0.861 0.032 0.19 -1.528
    Yoruba 0.033 0.415 -0.931 1.99 0.024
    Ami 1.345 -0.61 -0.698 -0.241 1.508
    A:
    scale 129.442 1326.304 2399.175 14751.57 21259.127
    Andronovo2 0.251 1.479 0.082 0.04 -1.655
    Scythian_IA 0.553 1.185 -1.036 0.986 1.116
    Chechen 0.07 0.559 -0.752 -1.984 0.425
    Saudi -0.417 -0.808 -1.83 0.265 -0.869
    Mongola 2.11 -0.665 -0.075 -0.145 -0.282


    best coefficients: 0.674 -0.77 0.598 0.341 0.157
    ssres:
    -0.000014936 -0.000454832 -0.000178677 -0.000155892 -0.000334797
    -0.05450867 -1.659900606 -0.652075749 -0.568925729 -1.221834488

    Jackknife mean: 0.337937311 -0.568627554 0.854770091 0.256126601 0.119793552
    std. errors: 0.866 0.577 1.385 0.492 0.098

    error covariance (* 1000000)
    750471 -94709 -1010867 316944 38161
    -94709 333040 -256007 61708 -44031
    -1010867 -256007 1918491 -634064 -17553
    316944 61708 -634064 241637 13774
    38161 -44031 -17553 13774 9649


    fixed pat wt dof chisq tail prob
    0 0 1 0.308 0 0.674 -0.77 0.598 0.341 0.157 infeasible
    1 1 2 2.537 0 35.367 9.86 -63.425 19.198 0 infeasible
    10 1 2 0.816 0 35.367 9.86 -63.425 19.198 0 infeasible
    100 1 2 0.48 0 1.018 -0.725 0 0.539 0.168 infeasible
    1000 1 2 1.94 0 2.284 0 -2.757 1.342 0.131 infeasible
    10000 1 2 1.178 0 0 -0.88 1.756 -0.021 0.145 infeasible
    11 2 3 5.875 0 -3.655 0.72 3.935 0 0 infeasible
    101 2 3 5.644 0 0.87 -0.159 0 0.288 0 infeasible
    110 2 3 3.106 0 3.569 -2.982 0 0 0.414 infeasible
    1001 2 3 3.151 0 8.853 0 -10.956 3.103 0 infeasible
    1010 2 3 5.836 0 -1.284 0 2.25 0 0.034 infeasible
    1100 2 3 3.949 0.267052 0.488 0 0 0.459 0.052
    10001 2 3 6.623 0 0 -0.393 1.592 -0.199 0 infeasible
    10010 2 3 1.182 0 0 -0.393 1.592 -0.199 0 infeasible
    10100 2 3 9.811 0 0 0.533 0 0.489 -0.022 infeasible
    11000 2 3 6.347 0.0959047 0 0 0.692 0.27 0.038
    111 3 4 6.682 0 1.691 -0.691 0 0 0 infeasible
    1011 3 4 6.288 0 1.691 -0.691 0 0 0 infeasible
    1101 3 4 5.843 0.211167 0.665 0 0 0.335 0
    1110 3 4 10.738 0 1.024 0 0 0 -0.024 infeasible
    10011 3 4 6.902 0 0 -0.181 1.181 0 0 infeasible
    10101 3 4 9.906 0.0420486 0 0.471 0 0.529 0
    10110 3 4 13.799 0 0 1.225 0 0 -0.225 infeasible
    11001 3 4 7.527 0.110533 0 0 0.875 0.125 0
    11010 3 4 8.573 0 0 0 1.001 0 -0.001 infeasible
    11100 3 4 17.29 0.00169761 0 0 0 0.864 0.136
    1111 4 5 11.106 0.0493232 1 0 0 0 0
    10111 4 5 34.994 1.51E-06 0 1 0 0 0
    11011 4 5 8.575 0.127245 0 0 1 0 0
    11101 4 5 57.635 3.74E-11 0 0 0 1 0
    11110 4 5 1118.337 0 0 0 0 0 1
    best pat: 0 0 - -
    best pat: 1 0 chi(nested): 2.229 p-value for nested model: 0.135472
    best pat: 1100 0.267052 chi(nested): 1.412 p-value for nested model: 0.234776
    best pat: 1101 0.211167 chi(nested): 1.894 p-value for nested model: 0.168699
    best pat: 11011 0.127245 chi(nested): 2.732 p-value for nested model: 0.0983427

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  7. #4
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    NO SAMPLE Andronovo2 Scythian_IA Chechen Saudi Mongola CHISQ TAIL PROBABILITY
    1 DMXX 59% 0% 0% 41% 0% 6.443 17%
    2 DMXX 46% 0% 0% 50% 4% 5.302 15%
    3 DMXX 0% 0% 100% 0% 0% 12.911 2%
    4 DMXX 100% 0% 0% 0% 0% 13.809 2%
    5 DMXX 0% 100% 0% 0% 0% 34.258 0%
    6 DMXX 0% 0% 0% 100% 0% 39.706 0%
    7 DMXX 0% 0% 0% 0% 100% 1162.819 0%

    0 .DMXX 1
    1 Andronovo2 1
    2 Scythian_IA 1
    3 Chechen 9
    4 Saudi 8
    5 Mongola 6
    6 MbutiPygmy 10
    7 Karitiana 12
    8 Onge 9
    9 Han 33
    10 Yoruba 70
    11 Ami 10
    jackknife block size: 0.05
    snps: 463351 indivs: 170
    number of blocks for block jackknife: 711
    dof (jackknife): 613.447
    numsnps used: 25478
    codimension 1
    f4info:
    f4rank: 4 dof: 1 chisq: 0.518 tail: 0.471699838 dofdiff: 3 chisqdiff: -0.518 taildiff: 1
    B:
    scale 1 1 1 1
    Karitiana 0.97 1.981 -0.112 -0.209
    Onge 0.599 -0.099 2.007 -0.167
    Han 1.366 -0.916 -0.054 0.216
    Yoruba 0.014 0.232 -0.25 2.118
    Ami 1.354 -0.414 -0.945 -0.628
    A:
    scale 127.602 1296.117 2177.738 11410.428
    Andronovo2 0.29 1.452 0.388 0.572
    Scythian_IA 0.556 1.273 -0.771 1.632
    Chechen 0.086 0.678 -0.703 -1.382
    Saudi -0.392 -0.604 -1.937 0.308
    Mongola 2.108 -0.67 -0.092 0.075


    full rank 1
    f4info:
    f4rank: 5 dof: 0 chisq: 0 tail: 1 dofdiff: 1 chisqdiff: 0.518 taildiff: 0.471699838
    B:
    scale 1 1 1 1 1
    Karitiana 0.97 1.984 -0.061 -0.264 0.224
    Onge 0.598 -0.129 2.064 0.318 -0.516
    Han 1.371 -0.865 -0.044 -0.154 1.532
    Yoruba 0.013 0.238 -0.242 2.185 0.335
    Ami 1.35 -0.493 -0.823 0.184 -1.491
    A:
    scale 128.458 1286.305 2119.986 10559.291 23102.873
    Andronovo2 0.26 1.5 0.124 -0.758 1.446
    Scythian_IA 0.559 1.241 -0.751 1.519 -0.527
    Chechen 0.081 0.672 -0.74 -1.429 -1.397
    Saudi -0.402 -0.58 -1.961 -0.068 0.806
    Mongola 2.11 -0.65 -0.161 -0.267 0.168


    best coefficients: 1.275 -0.854 -0.314 0.7 0.193
    ssres:
    -0.000079834 -0.000716403 -0.000302327 -0.000289331 -0.000622969
    -0.171551583 -1.539451471 -0.649658594 -0.621732859 -1.338675161

    Jackknife mean: 0.169665976 -0.518568345 0.943571298 0.293468524 0.111862546
    std. errors: 1.471 0.86 2.217 0.77 0.152

    error covariance (* 1000000)
    2163680 -353536 -2843925 911317 122465
    -353536 738783 -363009 83092 -105330
    -2843925 -363009 4914997 -1627276 -80787
    911317 83092 -1627276 592265 40602
    122465 -105330 -80787 40602 23051


    fixed pat wt dof chisq tail prob
    0 0 1 0.518 0 1.275 -0.854 -0.314 0.7 0.193 infeasible
    1 1 2 2.167 0 6.692 1.266 -10.474 3.516 0 infeasible
    10 1 2 1.729 0 6.692 1.266 -10.474 3.516 0 infeasible
    100 1 2 0.548 0 1.104 -0.887 0 0.594 0.189 infeasible
    1000 1 2 1.508 0 2.752 0 -3.568 1.676 0.14 infeasible
    10000 1 2 2.383 0 0 -1.291 2.172 -0.079 0.198 infeasible
    11 2 3 5.171 0 -6.546 1.519 6.027 0 0 infeasible
    101 2 3 5.704 0 0.962 -0.288 0 0.326 0 infeasible
    110 2 3 2.771 0 4.61 -4.192 0 0 0.582 infeasible
    1001 2 3 2.488 0 6.014 0 -7.361 2.346 0 infeasible
    1010 2 3 5.574 0 -2.573 0 3.506 0 0.067 infeasible
    1100 2 3 5.302 0.151 0.456 0 0 0.503 0.041
    10001 2 3 8.503 0 0 -0.715 2.072 -0.357 0 infeasible
    10010 2 3 2.409 0 0 -1.177 1.988 0 0.189 infeasible
    10100 2 3 11.446 0 0 0.501 0 0.525 -0.026 infeasible
    11000 2 3 8.719 0.0332751 0 0 0.576 0.385 0.038
    111 3 4 6.598 0 1.93 -0.93 0 0 0 infeasible
    1011 3 4 6.111 0 -2.165 0 3.165 0 0 infeasible
    1101 3 4 6.443 0.168445 0.591 0 0 0.409 0
    1110 3 4 12.523 0 1.046 0 0 0 -0.046 infeasible
    10011 3 4 8.842 0 0 -0.323 1.323 0 0 infeasible
    10101 3 4 11.542 0.0211011 0 0.418 0 0.582 0
    10110 3 4 14.186 0 0 1.234 0 0 -0.234 infeasible
    11001 3 4 9.901 0.0421319 0 0 0.758 0.242 0
    11010 3 4 12.672 0 0 0 1.013 0 -0.013 infeasible
    11100 3 4 16.111 0.00287356 0 0 0 0.887 0.113
    1111 4 5 13.809 0.0168697 1 0 0 0 0
    10111 4 5 34.258 2.12E-06 0 1 0 0 0
    11011 4 5 12.911 0.0242316 0 0 1 0 0
    11101 4 5 39.706 1.71E-07 0 0 0 1 0
    11110 4 5 1162.819 0 0 0 0 0 1
    best pat: 0 0 - -
    best pat: 1 0 chi(nested): 1.649 p-value for nested model: 0.199061
    best pat: 1100 0.151 chi(nested): 3.134 p-value for nested model: 0.0766595
    best pat: 1101 0.168445 chi(nested): 1.141 p-value for nested model: 0.285444
    best pat: 11011 0.0242316 chi(nested): 6.468 p-value for nested model: 0.0109836

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  9. #5
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    I am not sure if the results based on the average of several members (Iranian results) are directly comparable with individual member results, and as such the comparison between Iranian and individual members should be done with a grain of salt.


    NO SAMPLE ANDRONOVO 503 CHISQ TAIL PROBABILITY
    1 NK19191 100% 11.106 5%
    2 DMXX 100% 13.809 2%
    3 JESUS 100% 30.541 0%
    4 IRANIANS 100% 17.306 0%
    NO SAMPLE SCYTHIAN IA CHISQ TAIL PROBABILITY
    1 DMXX 100% 34.258 0%
    2 NK19191 100% 34.994 0%
    3 JESUS 100% 57.245 0%
    4 IRANIANS 100% 51 0%
    NO SAMPLE CHECHEN CHISQ TAIL PROBABILITY
    1 NK19191 100% 8.575 13%
    2 DMXX 100% 12.911 2%
    3 JESUS 100% 24.936 0%
    4 IRANIANS 100% 21.16 0%
    NO SAMPLE SAUDI CHISQ TAIL PROBABILITY
    1 JESUS 100% 4.851 43%
    2 DMXX 100% 39.706 0%
    3 NK19191 100% 57.635 0%
    4 IRANIANS 100% 136.846 0%
    NO SAMPLE MONGOLIAN CHISQ TAIL PROBABILITY
    1 NK19191 100% 1118.337 0%
    2 DMXX 100% 1162.819 0%
    3 JESUS 100% 1208.666 0%
    4 IRANIANS 100% 2501.581 0%

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  11. #6
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    Ibex retter; Der Nomad
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    Afghanistan United States of America Germany Greater Khorasan Dravida Nadu Azad Baluchistan
    How can Iranians show Saudi unless those Saudis have some Iranian ancestry? This is very strange!

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  13. #7
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    Iranians, like all west Asians, tend to show some ancient south west asian affinity/admixture.

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    Quote Originally Posted by surbakhunWeesste View Post
    How can Iranians show Saudi unless those Saudis have some Iranian ancestry? This is very strange!
    Iranians and some W Asian have considerable SW Asian admixture. It evens shows up with tools such as ADMIXTURE which are based on recent drift

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    Quote Originally Posted by Kurd View Post
    Iranians and some W Asian have considerable SW Asian admixture. It evens shows up with tools such as ADMIXTURE which are based on recent drift
    So those allele affinity is strictly the SW Asian component like?

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    Quote Originally Posted by surbakhunWeesste View Post
    So those allele affinity is strictly the SW Asian component like?
    Yes, and affinity seems to be there even with formal methods such as these that dig deeper in time. After all Saudi ancestors in general are probably a very likely admixing pop for Iranians

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