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Thread: An Ancient Harappan Genome Lacks Ancestry from Steppe Pastoralists or Iranian Farmers

  1. #1001
    Quote Originally Posted by pegasus View Post
    ANF is already in Iran 7-8 Kya , Steppe Eneolithic populations form a bit later and they are devoid of any ANF so that eliminates Iran_N as a source. Rather some variant of CHG is needed and one which left the North Caucasus earlier than when Maykop type populations formed who harbor a large amount of ANF.
    This is incorrect. Turan sources give acceptable models for Steppe eneolithic whereas only EHG+CHG is a failed model. The minor wshg and anatolian in turan is not a problem.

    left pops:
    Russia_Steppe_Eneolithic

    Russia_HG_Karelia: 47.5 +- 1.9
    Georgia_Kotias.SG: 24 +- 3.1
    Geoksyur_EN: 28.5+- 3.3
    pvalue 0.097
    result file https://pastebin.com/vc9v2kwP
    2 way models are a big fail

    even vahaduo fit improves when geoksyur is added as a source. geoksyur is just a proxy as these are oldest samples from the region. 4500bce samples from turan will have even lesser wshg and anatolian.

  2. #1002
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    Quote Originally Posted by misnomer View Post
    This is incorrect. Turan sources give acceptable models for Steppe eneolithic whereas only EHG+CHG is a failed model. The minor wshg and anatolian in turan is not a problem.

    left pops:
    Russia_Steppe_Eneolithic

    Russia_HG_Karelia: 47.5 +- 1.9
    Georgia_Kotias.SG: 24 +- 3.1
    Geoksyur_EN: 28.5+- 3.3
    pvalue 0.097
    result file https://pastebin.com/vc9v2kwP
    2 way models are a big fail

    even vahaduo fit improves when geoksyur is added as a source. geoksyur is just a proxy as these are oldest samples from the region. 4500bce samples from turan will have even lesser wshg and anatolian.
    Yes this is true with Chemurchek and Dali EBA, I think Sarazm would be better though have you tried it with that? Sarazm pretty much has 0 ANF.

    Though archaeologically speaking Geoksyur does not fit in that region at all and it has around 8-10 % ANF which I mentioned earlier , Steppe Eneolithic and even a few Afanasievo outliers have 0 to very little ANF. Thats what makes it difficult for any Eneolithic Central Asian farmers/ or even HGs to be part of the Yamnaya formation. Their ANF seems to be solely coming from GAC/TRB people and you see this in their uniparentals in Yamnaya. My guess is Sarazm is copensating for a more "Iran_N" like CHG variant which has yet to be documented OR there was an actual movement of Sarazm like people very early on. Though given dynamics of it all, and the people of the Eneolthic Steppe were not herding goats but fishing and eating Saiga antelopes , it points to the former theory though for now one can accept one with Sarazm. Geoksyur is just too out there IMO.

    "sample": "RUS_Progress_En:Average",
    "fit": 4.6054,
    "RUS_Sidelkino_HG": 48.33,
    "TJK_Sarazm_En": 29.17,
    "GEO_CHG": 22.5,
    "TKM_Geoksyur_En": 0,
    Last edited by pegasus; 04-25-2020 at 04:26 PM.

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  4. #1003
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    Afghanistan Jammu and Kashmir United States of America Canada
    ..........
    Last edited by pegasus; 04-25-2020 at 04:28 PM. Reason: double post

  5. #1004
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    7,822

    Quote Originally Posted by jdean View Post
    Think you've got the direction of flow wrong : )
    That is what is being argued about.

    One theory would be that the N Black Sea was Indo-Iranian with Indo-Aryan splitting there and moving east and south.

    Another would be that Indus Valley was Indo-Iranian with the Iranians splitting and moving west along with some Indo-Aryans. The Rg Ved includes many 'Iranian' tribes and the dispute of the phophet Zarathustra was with the Kavis and the Usij's of the Vedic Angira clan. Usijas https://books.google.com/books?id=xFyu7MANWPAC&pg=PA27

    Zarathustra left his original home of the three-castes (trizantu) and found his own followers in Balkh (Baktra) and beyond.

    "In Gathic vocabulary, Kavi meant a chief of a tribe, or a prince, a ruler and military chief of the socio-political organization among the Indo-Iranians ... Usig was probably the ritual performing priest who prepared and executed the sacrifice and offerings."
    https://www.cais-soas.com/CAIS/Relig...rathushtra.htm

    These followers from beyond are referred to as Iranians even though they had little to do with present day Iran.
    "Culture of who" "Furthermore, they seem to have shown little similarity with the Iranians of presentday Iran." https://books.google.com/books?id=MfW1AQAAQBAJ&pg=PT15

    Herodotus: "the wandering Scythians once dwelt in Asia, and there warred with the Massagetae, but with ill success; they therefore quitted their homes, crossed the Araxes, and entered the land of Cimmeria. For the land which is now inhabited by the Scyths was formerly the country of the Cimmerian"



    As vedic lines are patrilineal, per the genetic evidence we are seeing, if R1a1 is Rg Vedic/Indo-Iranian, then an origin in the region between the Black Sea and the Baltics is all but certain. But if the R1a1 folk were Indo-Iranized then perhaps not.
    Last edited by parasar; 04-25-2020 at 05:39 PM.

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  7. #1005
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    "Previously reported subclade for DA19 (E-Y31991>PF4428>Y134097) isn't correct, he seems to be some kind of pre-Y31991, with three derived and six ancestral SNPs at that level. In fact, he could very well belong to the same lineage as those seven IA Udegram samples from Narasimhan paper. Of nine total SNPs covered at Y31991 level, only three are also covered in Udegram samples, but all three are in favour of DA19 belonging to the same lineage."
    https://anthrogenica.com/showthread....l=1#post662040


    Quote Originally Posted by Pribislav View Post
    Those guys are not from the Balkans, how on earth did you come to that conclusion? They are partial/pre-Y31991 (~30% derived SNPs), so they belong to some really ancient split, that separated from the ancestor of modern Y31991 sometime during Paleolithic (~13500 BC by my calculations). So late UP split is pretty much a fact for these guys, the only question is when exactly, and from where, did they come to Swat Valley. And the Balkans surely isn't at the top of the list.
    Quote Originally Posted by Pribislav View Post
    I've merged the calls for all 7 E1b1b1b2 samples from Udegram_SPGT to get a better coverage, and they have 20 SNPs covered out of total 56 at Y31991 level, 6 of them being derived and 14 being ancestral. So I6900, I1799, I1985, I6194, I6197, I6899 and I3262 all belong to E1b1b1b2-M123>pre-Y31991
    Shak DA19 800-750BC
    mtDNA: U7a4
    Y-DNA: E (pre E-Y31991)

    Udegram graveyard, middle Swat valley
    "The samples are from an extensive graveyard in Udegram village in the Swat Valley dating to 1400-800 BCE. The graveyard of Udegram (32 excavated graves) features two burial phases, encompassing 1400-1100 cal BCE and 1000-800 cal BCE. One inter-phase documented mainly from a nearby graveyard at Gogdara IV (approximately 1200-900 cal BCE) is also represented at Udegram (51, 52). From the chrono-stratigraphic viewpoint, amongst the graves discussed in what follows, Graves 3, 5 28 (individual 1), and 29 belong to the oldest phase, Grave 6 possibly belong to the intermediate phase, while Graves 1, 7, 9, 10, 12, 26 and 27 belong to second phase (see figs. 226, 229 in ref. (51))."


    I6900 .. E1b1b1b2 Udegram_IA 1400-1126 cal BCE Pakistan
    S8190.E1.L1 U7a .. Udegram_IA 1200-800 BCE Pakistan

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  9. #1006
    Quote Originally Posted by pegasus View Post
    Yes this is true with Chemurchek and Dali EBA, I think Sarazm would be better though have you tried it with that? Sarazm pretty much has 0 ANF.

    Though archaeologically speaking Geoksyur does not fit in that region at all and it has around 8-10 % ANF which I mentioned earlier , Steppe Eneolithic and even a few Afanasievo outliers have 0 to very little ANF. Thats what makes it difficult for any Eneolithic Central Asian farmers/ or even HGs to be part of the Yamnaya formation. Their ANF seems to be solely coming from GAC/TRB people and you see this in their uniparentals in Yamnaya. My guess is Sarazm is copensating for a more "Iran_N" like CHG variant which has yet to be documented OR there was an actual movement of Sarazm like people very early on. Though given dynamics of it all, and the people of the Eneolthic Steppe were not herding goats but fishing and eating Saiga antelopes , it points to the former theory though for now one can accept one with Sarazm. Geoksyur is just too out there IMO.

    "sample": "RUS_Progress_En:Average",
    "fit": 4.6054,
    "RUS_Sidelkino_HG": 48.33,
    "TJK_Sarazm_En": 29.17,
    "GEO_CHG": 22.5,
    "TKM_Geoksyur_En": 0,
    Sarazm, parkhai, geoksyur, SiS - all work well

    Archaeological connection - 2019
    https://www.nature.com/articles/s41598-018-35758-w
    Intensification in pastoralist cereal use coincides with the expansion of trans-regional networks in the Eurasian Steppe

    After the initial domestication of wheat (Triticum sp.) and barley (Hordeum sp.) in southwest Asia by 8,500 cal BC, these cultivars spread into the Iranian Plateau by 6000 cal BC and into Pakistan by c. 5500 cal BC12,13,14,15. In southern Central Asia, domesticated forms of barley and wheat identified in Jeitun cultural contexts in Turkmenistan suggests these cultivars had spread to western Central Asia around 6100 cal BC16,17. Domesticated wheat and barley were cultivated in the southern Caucasus by c. 6000 cal BC18,19 and were present in the northern Caucasus by c. 4500 cal BC20. Wheat and barley spread into eastern Ukraine by 4000 cal BC and into the Crimean steppe by 3400 cal BC19.

  10. #1007
    Question:
    Has the south Asian specific y subclade R-Y3 with tmrca of 4600bp been found anywhere in the steppe? If not, why not?

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  12. #1008
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    Quote Originally Posted by misnomer View Post
    This is incorrect. Turan sources give acceptable models for Steppe eneolithic whereas only EHG+CHG is a failed model. The minor wshg and anatolian in turan is not a problem.

    left pops:
    Russia_Steppe_Eneolithic

    Russia_HG_Karelia: 47.5 +- 1.9
    Georgia_Kotias.SG: 24 +- 3.1
    Geoksyur_EN: 28.5+- 3.3
    pvalue 0.097
    result file https://pastebin.com/vc9v2kwP
    2 way models are a big fail

    even vahaduo fit improves when geoksyur is added as a source. geoksyur is just a proxy as these are oldest samples from the region. 4500bce samples from turan will have even lesser wshg and anatolian.
    The problem is because you have Kotias in the left and Satsurblia in the right. Kotias and Satsurblia form a clade to the exclusion of the CHG in the steppe.
    Central Asian pops 'work' as a supplemental source because on a global scale they are similar to CHG (both are mostly Iran_N-like with some ANE), and they help to artificially 'push' the Southern half of Steppe_Eneolithic out of the CHG-proper cluster.
    I've yet to test the idea, but I wonder if the cryptic CHG built into EHG may be the same thing as the CHG in later Steppe groups.
     

    /home/user/AdmixTools-master/bin/datasets/qpAdm1: parameter file: qpadmpar
    ### THE INPUT PARAMETERS
    ##PARAMETER NAME: VALUE
    genotypename: dataset18a.geno
    snpname: dataset18a.snp
    indivname: dataset18a.ind
    popleft: qpadmleft
    popright: qpadmright
    details: YES
    ## qpAdm version: 634
    seed: 536408970

    left pops:
    Steppe_Eneolithic
    EHG
    AG3
    Kotias

    right pops:
    Barcin_N
    Levant_N
    Iran_N
    Taforalt
    MA1
    ANA
    Iron_Gates_HG
    Sunghir
    Ami
    Onge
    Ust_Ishim

    0 Steppe_Eneolithic 3
    1 EHG 3
    2 AG3 1
    3 Kotias 1
    4 Barcin_N 5
    5 Levant_N 2
    6 Iran_N 7
    7 Taforalt 5
    8 MA1 1
    9 ANA 2
    10 Iron_Gates_HG 5
    11 Sunghir 4
    12 Ami 3
    13 Onge 11
    14 Ust_Ishim 1
    jackknife block size: 0.050
    snps: 1150054 indivs: 54
    number of blocks for block jackknife: 713
    ## ncols: 1150054
    coverage: Steppe_Eneolithic 1016711
    coverage: EHG 1139035
    coverage: AG3 265526
    coverage: Kotias 1148437
    coverage: Barcin_N 1118746
    coverage: Levant_N 787915
    coverage: Iran_N 1149137
    coverage: Taforalt 1091065
    coverage: MA1 805532
    coverage: ANA 1146873
    coverage: Iron_Gates_HG 1042593
    coverage: Sunghir 1149279
    coverage: Ami 616682
    coverage: Onge 572042
    coverage: Ust_Ishim 1147177
    dof (jackknife): 606.493
    numsnps used: 200189
    codimension 1
    f4info:
    f4rank: 2 dof: 8 chisq: 4.890 tail: 0.769246011 dofdiff: 10 chisqdiff: -4.890 taildiff: 1
    B:
    scale 1.000 1.000
    Levant_N -0.055 0.430
    Iran_N -0.047 1.651
    Taforalt 0.457 0.308
    MA1 2.376 0.290
    ANA 1.547 -0.171
    Iron_Gates_HG 0.663 -2.504
    Sunghir 0.541 -0.453
    Ami 0.600 0.176
    Onge 0.583 0.421
    Ust_Ishim 0.562 0.444
    A:
    scale 494.281 2017.156
    EHG 0.393 -1.378
    AG3 1.551 0.726
    Kotias -0.663 0.758


    full rank
    f4info:
    f4rank: 3 dof: 0 chisq: 0.000 tail: 1 dofdiff: 8 chisqdiff: 4.890 taildiff: 0.769246011
    B:
    scale 1.000 1.000 1.000
    Levant_N -0.055 0.420 -1.175
    Iran_N -0.045 1.635 -1.694
    Taforalt 0.461 0.315 0.388
    MA1 2.381 0.251 -1.063
    ANA 1.545 -0.199 0.928
    Iron_Gates_HG 0.657 -2.524 0.823
    Sunghir 0.539 -0.455 1.463
    Ami 0.599 0.178 0.441
    Onge 0.580 0.408 -0.253
    Ust_Ishim 0.557 0.416 0.727
    A:
    scale 492.726 1936.156 7342.191
    EHG 0.384 -1.195 0.809
    AG3 1.552 0.812 0.751
    Kotias -0.665 0.956 1.335


    best coefficients: 0.353 0.131 0.516
    Jackknife mean: 0.352864252 0.131575452 0.515560296
    std. errors: 0.046 0.035 0.027

    error covariance (* 1000000)
    2094 -1304 -790
    -1304 1259 45
    -790 45 745


    summ: Steppe_Eneolithic 3 0.769246 0.353 0.132 0.516 2094 -1304 -790 1259 45 745

    fixed pat wt dof chisq tail prob
    000 0 8 4.890 0.769246 0.353 0.131 0.516
    001 1 9 274.208 0 1.479 -0.479 -0.000 infeasible
    010 1 9 17.971 0.0355152 0.484 0.000 0.516
    100 1 9 50.531 8.55719e-08 -0.000 0.344 0.656
    011 2 10 295.179 0 1.000 0.000 -0.000
    101 2 10 445.729 0 0.000 1.000 -0.000
    110 2 10 177.490 0 0.000 0.000 1.000
    best pat: 000 0.769246 - -
    best pat: 010 0.0355152 chi(nested): 13.080 p-value for nested model: 0.000298387
    best pat: 110 7.77358e-33 chi(nested): 159.520 p-value for nested model: 1.44077e-36

    coeffs: 0.353 0.131 0.516

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

    details: EHG Levant_N -0.000443 -1.965288
    details: AG3 Levant_N -0.000107 -0.360651
    details: Kotias Levant_N 0.000053 0.161655
    dscore: Levant_N f4: -0.000143 Z: -0.646428

    details: EHG Iran_N -0.001194 -6.879348
    details: AG3 Iran_N 0.000397 1.681357
    details: Kotias Iran_N 0.000600 2.432215
    dscore: Iran_N f4: -0.000059 Z: -0.352826

    details: EHG Taforalt 0.000232 1.051856
    details: AG3 Taforalt 0.001665 5.767704
    details: Kotias Taforalt -0.000357 -1.187502
    dscore: Taforalt f4: 0.000116 Z: 0.554416

    details: EHG MA1 0.001585 5.473918
    details: AG3 MA1 0.007534 17.713886
    details: Kotias MA1 -0.003302 -8.330729
    dscore: MA1 f4: -0.000155 Z: -0.568740

    details: EHG ANA 0.001486 5.451666
    details: AG3 ANA 0.004953 13.893429
    details: Kotias ANA -0.001969 -5.620336
    dscore: ANA f4: 0.000159 Z: 0.648961

    details: EHG Iron_Gates_HG 0.002198 10.736174
    details: AG3 Iron_Gates_HG 0.001128 4.403042
    details: Kotias Iron_Gates_HG -0.001954 -7.633797
    dscore: Iron_Gates_HG f4: -0.000084 Z: -0.459131

    details: EHG Sunghir 0.000887 4.181540
    details: AG3 Sunghir 0.001684 6.077475
    details: Kotias Sunghir -0.000675 -2.466280
    dscore: Sunghir f4: 0.000186 Z: 0.963401

    details: EHG Ami 0.000437 2.053037
    details: AG3 Ami 0.002050 7.241543
    details: Kotias Ami -0.000602 -2.056428
    dscore: Ami f4: 0.000113 Z: 0.565318

    details: EHG Onge 0.000207 0.953476
    details: AG3 Onge 0.002009 7.310063
    details: Kotias Onge -0.000592 -2.054224
    dscore: Onge f4: 0.000032 Z: 0.158888

    details: EHG Ust_Ishim 0.000292 1.179003
    details: AG3 Ust_Ishim 0.002028 6.087088
    details: Kotias Ust_Ishim -0.000385 -1.211831
    dscore: Ust_Ishim f4: 0.000171 Z: 0.750115

    gendstat: Barcin_N Levant_N -0.646
    gendstat: Barcin_N Iran_N -0.353
    gendstat: Barcin_N Taforalt 0.554
    gendstat: Barcin_N MA1 -0.569
    gendstat: Barcin_N ANA 0.649
    gendstat: Barcin_N Iron_Gates_HG -0.459
    gendstat: Barcin_N Sunghir 0.963
    gendstat: Barcin_N Ami 0.565
    gendstat: Barcin_N Onge 0.159
    gendstat: Barcin_N Ust_Ishim 0.750
    gendstat: Levant_N Iran_N 0.366
    gendstat: Levant_N Taforalt 0.975
    gendstat: Levant_N MA1 -0.036
    gendstat: Levant_N ANA 0.993
    gendstat: Levant_N Iron_Gates_HG 0.234
    gendstat: Levant_N Sunghir 1.332
    gendstat: Levant_N Ami 0.964
    gendstat: Levant_N Onge 0.681
    gendstat: Levant_N Ust_Ishim 1.085
    gendstat: Iran_N Taforalt 0.810
    gendstat: Iran_N MA1 -0.358
    gendstat: Iran_N ANA 0.898
    gendstat: Iran_N Iron_Gates_HG -0.128
    gendstat: Iran_N Sunghir 1.255
    gendstat: Iran_N Ami 0.914
    gendstat: Iran_N Onge 0.498
    gendstat: Iran_N Ust_Ishim 1.036
    gendstat: Taforalt MA1 -0.898
    gendstat: Taforalt ANA 0.161
    gendstat: Taforalt Iron_Gates_HG -0.901
    gendstat: Taforalt Sunghir 0.311
    gendstat: Taforalt Ami -0.015
    gendstat: Taforalt Onge -0.371
    gendstat: Taforalt Ust_Ishim 0.211
    gendstat: MA1 ANA 1.041
    gendstat: MA1 Iron_Gates_HG 0.261
    gendstat: MA1 Sunghir 1.248
    gendstat: MA1 Ami 0.941
    gendstat: MA1 Onge 0.680
    gendstat: MA1 Ust_Ishim 1.076
    gendstat: ANA Iron_Gates_HG -0.936
    gendstat: ANA Sunghir 0.108
    gendstat: ANA Ami -0.200
    gendstat: ANA Onge -0.532
    gendstat: ANA Ust_Ishim 0.043
    gendstat: Iron_Gates_HG Sunghir 1.372
    gendstat: Iron_Gates_HG Ami 0.903
    gendstat: Iron_Gates_HG Onge 0.549
    gendstat: Iron_Gates_HG Ust_Ishim 1.015
    gendstat: Sunghir Ami -0.357
    gendstat: Sunghir Onge -0.778
    gendstat: Sunghir Ust_Ishim -0.064
    gendstat: Ami Onge -0.452
    gendstat: Ami Ust_Ishim 0.247
    gendstat: Onge Ust_Ishim 0.595

    ## end of run
    Last edited by Kale; 04-26-2020 at 02:10 AM.
    Collection of 14,000 d-stats: Hidden Content Part 2: Hidden Content Part 3: Hidden Content PM me for d-stats, qpadm, qpgraph, or f3-outgroup nmonte models.

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  14. #1009
    Quote Originally Posted by Kale View Post
    The problem is because you have Kotias in the left and Satsurblia in the right. Kotias and Satsurblia form a clade to the exclusion of the CHG in the steppe.
    Central Asian pops 'work' as a supplemental source because on a global scale they are similar to CHG (both are mostly Iran_N-like with some ANE), and they help to artificially 'push' the Southern half of Steppe_Eneolithic out of the CHG-proper cluster.
    I've yet to test the idea, but I wonder if the cryptic CHG built into EHG may be the same thing as the CHG in later Steppe groups.
     

    /home/user/AdmixTools-master/bin/datasets/qpAdm1: parameter file: qpadmpar
    ### THE INPUT PARAMETERS
    ##PARAMETER NAME: VALUE
    genotypename: dataset18a.geno
    snpname: dataset18a.snp
    indivname: dataset18a.ind
    popleft: qpadmleft
    popright: qpadmright
    details: YES
    ## qpAdm version: 634
    seed: 536408970

    left pops:
    Steppe_Eneolithic
    EHG
    AG3
    Kotias

    right pops:
    Barcin_N
    Levant_N
    Iran_N
    Taforalt
    MA1
    ANA
    Iron_Gates_HG
    Sunghir
    Ami
    Onge
    Ust_Ishim

    0 Steppe_Eneolithic 3
    1 EHG 3
    2 AG3 1
    3 Kotias 1
    4 Barcin_N 5
    5 Levant_N 2
    6 Iran_N 7
    7 Taforalt 5
    8 MA1 1
    9 ANA 2
    10 Iron_Gates_HG 5
    11 Sunghir 4
    12 Ami 3
    13 Onge 11
    14 Ust_Ishim 1
    jackknife block size: 0.050
    snps: 1150054 indivs: 54
    number of blocks for block jackknife: 713
    ## ncols: 1150054
    coverage: Steppe_Eneolithic 1016711
    coverage: EHG 1139035
    coverage: AG3 265526
    coverage: Kotias 1148437
    coverage: Barcin_N 1118746
    coverage: Levant_N 787915
    coverage: Iran_N 1149137
    coverage: Taforalt 1091065
    coverage: MA1 805532
    coverage: ANA 1146873
    coverage: Iron_Gates_HG 1042593
    coverage: Sunghir 1149279
    coverage: Ami 616682
    coverage: Onge 572042
    coverage: Ust_Ishim 1147177
    dof (jackknife): 606.493
    numsnps used: 200189
    codimension 1
    f4info:
    f4rank: 2 dof: 8 chisq: 4.890 tail: 0.769246011 dofdiff: 10 chisqdiff: -4.890 taildiff: 1
    B:
    scale 1.000 1.000
    Levant_N -0.055 0.430
    Iran_N -0.047 1.651
    Taforalt 0.457 0.308
    MA1 2.376 0.290
    ANA 1.547 -0.171
    Iron_Gates_HG 0.663 -2.504
    Sunghir 0.541 -0.453
    Ami 0.600 0.176
    Onge 0.583 0.421
    Ust_Ishim 0.562 0.444
    A:
    scale 494.281 2017.156
    EHG 0.393 -1.378
    AG3 1.551 0.726
    Kotias -0.663 0.758


    full rank
    f4info:
    f4rank: 3 dof: 0 chisq: 0.000 tail: 1 dofdiff: 8 chisqdiff: 4.890 taildiff: 0.769246011
    B:
    scale 1.000 1.000 1.000
    Levant_N -0.055 0.420 -1.175
    Iran_N -0.045 1.635 -1.694
    Taforalt 0.461 0.315 0.388
    MA1 2.381 0.251 -1.063
    ANA 1.545 -0.199 0.928
    Iron_Gates_HG 0.657 -2.524 0.823
    Sunghir 0.539 -0.455 1.463
    Ami 0.599 0.178 0.441
    Onge 0.580 0.408 -0.253
    Ust_Ishim 0.557 0.416 0.727
    A:
    scale 492.726 1936.156 7342.191
    EHG 0.384 -1.195 0.809
    AG3 1.552 0.812 0.751
    Kotias -0.665 0.956 1.335


    best coefficients: 0.353 0.131 0.516
    Jackknife mean: 0.352864252 0.131575452 0.515560296
    std. errors: 0.046 0.035 0.027

    error covariance (* 1000000)
    2094 -1304 -790
    -1304 1259 45
    -790 45 745


    summ: Steppe_Eneolithic 3 0.769246 0.353 0.132 0.516 2094 -1304 -790 1259 45 745

    fixed pat wt dof chisq tail prob
    000 0 8 4.890 0.769246 0.353 0.131 0.516
    001 1 9 274.208 0 1.479 -0.479 -0.000 infeasible
    010 1 9 17.971 0.0355152 0.484 0.000 0.516
    100 1 9 50.531 8.55719e-08 -0.000 0.344 0.656
    011 2 10 295.179 0 1.000 0.000 -0.000
    101 2 10 445.729 0 0.000 1.000 -0.000
    110 2 10 177.490 0 0.000 0.000 1.000
    best pat: 000 0.769246 - -
    best pat: 010 0.0355152 chi(nested): 13.080 p-value for nested model: 0.000298387
    best pat: 110 7.77358e-33 chi(nested): 159.520 p-value for nested model: 1.44077e-36

    coeffs: 0.353 0.131 0.516

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

    details: EHG Levant_N -0.000443 -1.965288
    details: AG3 Levant_N -0.000107 -0.360651
    details: Kotias Levant_N 0.000053 0.161655
    dscore: Levant_N f4: -0.000143 Z: -0.646428

    details: EHG Iran_N -0.001194 -6.879348
    details: AG3 Iran_N 0.000397 1.681357
    details: Kotias Iran_N 0.000600 2.432215
    dscore: Iran_N f4: -0.000059 Z: -0.352826

    details: EHG Taforalt 0.000232 1.051856
    details: AG3 Taforalt 0.001665 5.767704
    details: Kotias Taforalt -0.000357 -1.187502
    dscore: Taforalt f4: 0.000116 Z: 0.554416

    details: EHG MA1 0.001585 5.473918
    details: AG3 MA1 0.007534 17.713886
    details: Kotias MA1 -0.003302 -8.330729
    dscore: MA1 f4: -0.000155 Z: -0.568740

    details: EHG ANA 0.001486 5.451666
    details: AG3 ANA 0.004953 13.893429
    details: Kotias ANA -0.001969 -5.620336
    dscore: ANA f4: 0.000159 Z: 0.648961

    details: EHG Iron_Gates_HG 0.002198 10.736174
    details: AG3 Iron_Gates_HG 0.001128 4.403042
    details: Kotias Iron_Gates_HG -0.001954 -7.633797
    dscore: Iron_Gates_HG f4: -0.000084 Z: -0.459131

    details: EHG Sunghir 0.000887 4.181540
    details: AG3 Sunghir 0.001684 6.077475
    details: Kotias Sunghir -0.000675 -2.466280
    dscore: Sunghir f4: 0.000186 Z: 0.963401

    details: EHG Ami 0.000437 2.053037
    details: AG3 Ami 0.002050 7.241543
    details: Kotias Ami -0.000602 -2.056428
    dscore: Ami f4: 0.000113 Z: 0.565318

    details: EHG Onge 0.000207 0.953476
    details: AG3 Onge 0.002009 7.310063
    details: Kotias Onge -0.000592 -2.054224
    dscore: Onge f4: 0.000032 Z: 0.158888

    details: EHG Ust_Ishim 0.000292 1.179003
    details: AG3 Ust_Ishim 0.002028 6.087088
    details: Kotias Ust_Ishim -0.000385 -1.211831
    dscore: Ust_Ishim f4: 0.000171 Z: 0.750115

    gendstat: Barcin_N Levant_N -0.646
    gendstat: Barcin_N Iran_N -0.353
    gendstat: Barcin_N Taforalt 0.554
    gendstat: Barcin_N MA1 -0.569
    gendstat: Barcin_N ANA 0.649
    gendstat: Barcin_N Iron_Gates_HG -0.459
    gendstat: Barcin_N Sunghir 0.963
    gendstat: Barcin_N Ami 0.565
    gendstat: Barcin_N Onge 0.159
    gendstat: Barcin_N Ust_Ishim 0.750
    gendstat: Levant_N Iran_N 0.366
    gendstat: Levant_N Taforalt 0.975
    gendstat: Levant_N MA1 -0.036
    gendstat: Levant_N ANA 0.993
    gendstat: Levant_N Iron_Gates_HG 0.234
    gendstat: Levant_N Sunghir 1.332
    gendstat: Levant_N Ami 0.964
    gendstat: Levant_N Onge 0.681
    gendstat: Levant_N Ust_Ishim 1.085
    gendstat: Iran_N Taforalt 0.810
    gendstat: Iran_N MA1 -0.358
    gendstat: Iran_N ANA 0.898
    gendstat: Iran_N Iron_Gates_HG -0.128
    gendstat: Iran_N Sunghir 1.255
    gendstat: Iran_N Ami 0.914
    gendstat: Iran_N Onge 0.498
    gendstat: Iran_N Ust_Ishim 1.036
    gendstat: Taforalt MA1 -0.898
    gendstat: Taforalt ANA 0.161
    gendstat: Taforalt Iron_Gates_HG -0.901
    gendstat: Taforalt Sunghir 0.311
    gendstat: Taforalt Ami -0.015
    gendstat: Taforalt Onge -0.371
    gendstat: Taforalt Ust_Ishim 0.211
    gendstat: MA1 ANA 1.041
    gendstat: MA1 Iron_Gates_HG 0.261
    gendstat: MA1 Sunghir 1.248
    gendstat: MA1 Ami 0.941
    gendstat: MA1 Onge 0.680
    gendstat: MA1 Ust_Ishim 1.076
    gendstat: ANA Iron_Gates_HG -0.936
    gendstat: ANA Sunghir 0.108
    gendstat: ANA Ami -0.200
    gendstat: ANA Onge -0.532
    gendstat: ANA Ust_Ishim 0.043
    gendstat: Iron_Gates_HG Sunghir 1.372
    gendstat: Iron_Gates_HG Ami 0.903
    gendstat: Iron_Gates_HG Onge 0.549
    gendstat: Iron_Gates_HG Ust_Ishim 1.015
    gendstat: Sunghir Ami -0.357
    gendstat: Sunghir Onge -0.778
    gendstat: Sunghir Ust_Ishim -0.064
    gendstat: Ami Onge -0.452
    gendstat: Ami Ust_Ishim 0.247
    gendstat: Onge Ust_Ishim 0.595

    ## end of run
    The thing is that CHG + EHG just does not work for steppe_en in qpAdm. but CHG + EHG + turan does. thats just how it is.
    CHG + Turan just represents Steppe_Eneolithic better



    Last edited by misnomer; 04-26-2020 at 10:21 AM.

  15. #1010
    Gold Class Member
    Posts
    7,822

    Quote Originally Posted by misnomer View Post
    Question:
    Has the south Asian specific y subclade R-Y3 with tmrca of 4600bp been found anywhere in the steppe? If not, why not?
    I6561 4000 BC Y3+ Y2- is the only other known Y3 prior to Roopkund.

    "The currently oldest sample with Anatolian Farmer ancestry in the steppes in an individual at Aleksandriya, a Sredni Stog cemetery on the Donets in eastern Ukraine. Sredni Stog has often been discussed
    as a possible Yamnaya ancestor in Ukraine (Anthony 2007: 239-254). The single published grave is dated about 4000 BC (4045–3974 calBC/ 521520 BP/ PSUAMS-2832) and shows 20% Anatolian Farmer ancestry and 80% Khvalynsk-type steppe ancestry (CHG&EHG). His Y-chromosome haplogroup was R1a-Z93, similar to the later Sintashta culture and to South Asian Indo-Aryans, and he is the earliest known sample to
    show the genetic adaptation to lactase persistence (I3910-T)."
    Archaeology, Genetics, and Language in the Steppes
    David W. Anthony

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