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Thread: Making drift-free northern European(Celtic, Baltic, Scandinavian, and Slavic) samples

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    Making drift-free northern European(Celtic, Baltic, Scandinavian, and Slavic) samples

    Today I embarked on a project which was to recreate the G25 averages from northwestern, northern, and eastern Europe without drift and see how they score. It has been a mystery to a lot of people why eastern Europeans, in spite of having about as much Bronze Age steppe as NW/N Euros, do not seem to be closer to the ancient steppe groups despite their additional EHG rich ancestry and the fact that the Urheimat of Indo-Europeans was in eastern Europe. Some argued that it's because of Baltic HG ancestry which makes no sense as it can be modeled well as a mix of EHG and WHG and extremely well as a mix of Norwegian HG and WHG. The real culprit is simply post-Corded Ware drift. All of the groups originating in the northern European plain from Slavs to Celts descend from the Corded Ware culture and following its breakup, there has been a substantial bottleneck among Balto-Slavic populations which makes them act strangely on G25. While they cannot be modeled to a low fit without using Baltic_BA, you can still get reliable values for ancestral components. I used this fact to create drift-less versions of the averages for various groups.

    These are the ancients(all averages) I used to construct these ghost samples:

    Code:
    Baltic_LVA_HG,0.1292603,0.1004104,0.1802636,0.1972329,0.1064236,0.0560919,0.0083574,0.0207106,0.0524476,-0.0261394,-0.0046788,-0.0181151,0.0281434,-0.0053759,0.0355759,0.0480141,0.003072,0.0040856,-0.0059236,0.042325,0.0613526,0.0130531,-0.0262979,-0.1110549,0.0095949
    Corded_Ware_CZE,0.1235794,0.11548,0.0543053,0.0784429,0.0129254,0.0249007,0.0030886,0.0019119,-0.018641,-0.0284549,-0.002018,0.0014771,-0.0070721,-0.0185596,0.0222194,0.0103987,0.000447,0.0010679,0.004561,0.0077359,0.0002496,-0.0014663,0.0028876,0.0073159,-0.0004619
    POL_Globular_Amphora,0.1263436,0.1689961,0.0604725,-0.020045,0.0843053,-0.017849,0.0016865,0.0077916,0.0537897,0.0705682,0.0004012,0.0095386,-0.0161428,-0.0056101,-0.0098915,0.0004289,0.0045635,0.0068486,0.0062036,-0.000846,0.0091822,0.0078046,-0.013956,-0.0272541,0.0009228
    RUS_Sidelkino_HG,0.118376,0.039606,0.133501,0.195739,0.001846,0.054105,-0.019271,-0.018922,-0.0045,-0.071437,0.010068,-0.012139,0.030475,-0.043351,0.027008,0.02201,-0.002738,-0.003927,-0.008547,0.019509,-0.003868,0.011623,0.005546,-0.022413,-0.001796
    SWE_Motala_HG,0.13249,0.0895696,0.1651034,0.187341,0.0864774,0.0551646,-0.00235,0.008538,0.0376324,-0.0389258,0.0016562,-0.0187034,0.0310404,-0.0173406,0.0315686,0.049297,0.005763,0.0024324,-0.006335,0.039744,0.0507604,0.014418,-0.022086,-0.0977008,0.0070412
    And these are the resulting drift free averages:
    Code:
    Belarus_driftless,0.124628156,0.123529045,0.067746975,0.072553474,0.034793846,0.020347991,0.003355369,0.004800759,0.001218347,-0.010601869,-0.001848141,0.000992011,-0.005235566,-0.014962586,0.017812597,0.012310385,0.001436987,0.002392599,0.003825892,0.009598054,0.007827697,0.001606821,-0.00297074,-0.010437898,0.000770143
    Irish_driftless,0.124358904,0.13057154,0.05604445,0.050669312,0.033054532,0.012845285,0.002693208,0.003569975,0.001784457,-0.000530386,-0.001335786,0.003750443,-0.009630037,-0.014907841,0.013164126,0.007587216,0.001607853,0.002698057,0.005024213,0.005315804,0.002768593,0.001148094,-0.001862295,-0.00243284,-7.14146E-05
    Lith_driftless,0.124839073,0.117858264,0.077053678,0.090092077,0.036090794,0.026371879,0.003884111,0.005773163,0.000679079,-0.018739201,-0.002258896,-0.001213346,-0.001726818,-0.015022016,0.021551719,0.016081849,0.001295951,0.002142401,0.002870115,0.013016883,0.011843392,0.001960579,-0.003832346,-0.016766941,0.001438259
    Norwegian_driftless,0.124201502,0.128170687,0.058054201,0.054506914,0.032195428,0.013946594,0.002123075,0.002981256,0.001572678,-0.002440105,-0.001040903,0.003331932,-0.008581247,-0.015656013,0.013545517,0.007968869,0.001492111,0.002521944,0.004670264,0.00569056,0.002590075,0.001414248,-0.001658428,-0.002929231,-0.000117179
    RusKurk_driftless,0.1243377,0.120837629,0.06435706,0.070872647,0.02929807,0.019862149,0.001656227,0.002493207,-0.001966756,-0.012696467,-0.000903207,0.001350263,-0.005239233,-0.017131059,0.017052919,0.01107136,0.001345235,0.001991145,0.003769041,0.008309339,0.004337191,0.001570559,-0.001370226,-0.005625864,0.000126913
    RusOrel_driftless,0.124427782,0.122283278,0.063468383,0.068480215,0.030144822,0.019084201,0.001910521,0.00280201,-0.001412141,-0.01119045,-0.001024047,0.001594271,-0.005780506,-0.016704067,0.016674346,0.010832326,0.00142462,0.002108891,0.003942763,0.008082243,0.004475928,0.001506197,-0.001570563,-0.005614818,0.000156769
    Scottish_driftless,0.124397603,0.131320766,0.056130791,0.049290482,0.03405385,0.012246789,0.002673578,0.003652291,0.002798487,0.000855938,-0.001301917,0.003863304,-0.009757027,-0.014726548,0.012714574,0.007447639,0.001665484,0.002778987,0.00504721,0.005195658,0.00289365,0.001277886,-0.002098106,-0.00291682,-5.2288E-05
    Swedish_driftless,0.124514881,0.12808893,0.061376931,0.059244661,0.034741536,0.015671187,0.002972706,0.004197208,0.002449712,-0.003795289,-0.001535114,0.002614295,-0.007772152,-0.014768041,0.014843583,0.009581267,0.001583392,0.002634292,0.004507042,0.007129509,0.005153417,0.001471737,-0.002573775,-0.006465775,0.000324005
    Ukrainian_driftless,0.124663168,0.125747348,0.061632847,0.062853035,0.032458026,0.017215516,0.002489258,0.003551484,0.000187656,-0.007433293,-0.001292208,0.00214476,-0.006991438,-0.015670783,0.015724081,0.010325792,0.001631461,0.002401776,0.004330703,0.007593483,0.00492449,0.001412508,-0.002132879,-0.005891262,0.000245132
    Note:The Lithuanian and Belarusian samples still act a bit strangely, not scoring nearly as much steppe and instead a lot more EHG than the other groups. I was about to put Orcadian too but I realized they scored exactly like Scots. Both Scots and Irish could be modeled solely with GAC and CWC with no need for another neolithic or HG source.


    These are the distances between the modified averages and some ancients:

    Distance to: Yamnaya_RUS_Samara
    0.12414500 RusKurk_driftless
    0.12458764 Lith_driftless
    0.12693257 RusOrel_driftless
    0.13130059 Belarus_driftless
    0.13417359 Ukrainian_driftless
    0.14077937 Swedish_driftless
    0.14141608 Norwegian_driftless
    0.14542513 Irish_driftless
    0.14812134 Scottish_driftless

    Distance to: KAZ_Oy_Dzhaylau_MLBA
    0.06068774 RusKurk_driftless
    0.06347598 RusOrel_driftless
    0.06738855 Lith_driftless
    0.06883003 Belarus_driftless
    0.07079592 Ukrainian_driftless
    0.07712838 Swedish_driftless
    0.07764722 Norwegian_driftless
    0.08231356 Irish_driftless
    0.08482522 Scottish_driftless

    Distance to: Corded_Ware_CZE
    0.03547028 RusKurk_driftless
    0.03756841 RusOrel_driftless
    0.04391400 Ukrainian_driftless
    0.04434014 Belarus_driftless
    0.05026287 Swedish_driftless
    0.05069871 Norwegian_driftless
    0.05070600 Lith_driftless
    0.05485964 Irish_driftless
    0.05758317 Scottish_driftless

    Distance to: RUS_Sintashta_MLBA
    0.03906117 RusKurk_driftless
    0.04119095 RusOrel_driftless
    0.04748920 Ukrainian_driftless
    0.04759819 Belarus_driftless
    0.05302777 Lith_driftless
    0.05358252 Swedish_driftless
    0.05394456 Norwegian_driftless
    0.05815731 Irish_driftless
    0.06077744 Scottish_driftless

    These are the distances between the unmodified averages and the ancients:


    Distance to: Yamnaya_RUS_Samara
    0.13902410 Russian_Kursk
    0.14158761 Russian_Orel
    0.14529528 Swedish
    0.14596925 Norwegian
    0.14688741 Lithuanian_PZ
    0.14743125 Ukrainian
    0.14842935 Belarusian
    0.14944880 Irish
    0.15170849 Scottish

    Distance to: KAZ_Oy_Dzhaylau_MLBA
    0.08298645 Norwegian
    0.08386049 Swedish
    0.08551963 Russian_Kursk
    0.08864237 Russian_Orel
    0.08943810 Irish
    0.09088881 Scottish
    0.09299165 Ukrainian
    0.09701585 Belarusian
    0.10362979 Lithuanian_PZ

    Distance to: Corded_Ware_CZE
    0.05866715 Swedish
    0.05953010 Norwegian
    0.06268939 Irish
    0.06408368 Scottish
    0.07103239 Russian_Kursk
    0.07239572 Russian_Orel
    0.07414493 Ukrainian
    0.08065480 Belarusian
    0.09055699 Lithuanian_PZ

    Distance to: RUS_Sintashta_MLBA
    0.05958175 Norwegian
    0.05959307 Swedish
    0.06345206 Irish
    0.06480689 Scottish
    0.07150357 Russian_Kursk
    0.07316148 Russian_Orel
    0.07519291 Ukrainian
    0.08054015 Belarusian
    0.08972688 Lithuanian_PZ


    As you can see, all of the distances are greater without the modification but this is only to be expected. However, the most glaring disparities in fit distance between drift vs no drift is among the eastern Europeans, who go from being the furthest to the closest matches and their distances cut by well over 50%!
    Last edited by Cynic; 07-28-2021 at 06:24 PM. Reason: forgot to include Belarusians

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  3. #2
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    Very interesting stuff.

    Can you elaborate more as to why you think this is happening?
    dosas: 56.25% Greek_Macedonia + 43.75% Greek_Trabzon @ 1.769
    wife: 50% English + 50% Irish @ 1.837
    kid1: 56.25% English + 43.75% Greek_Cappadocia @ 1.817
    kid2: 56.25% English_Cornwall + 43.75% Greek_Cappadocia @ 1.866

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     Cynic (07-28-2021)

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    Quote Originally Posted by dosas View Post
    Very interesting stuff.

    Can you elaborate more as to why you think this is happening?
    Why do I think what is happening? The drift?

    Well it appears that at some point the ancestors of modern day Baltic, Slavic, and even Finns seem to have undergone a bottleneck wherein they were isolated from other Europeans without any gene flow between them and this interrupted what would otherwise have been a perfect genetic continuum across Europe. All groups have some drift within the last few thousand years but it seems particularly high among eastern Europeans, they almost form their own component. Or at the very least, G25 seems to exaggerate this effect. Whatever the case may be, I wanted to test out my hypothesis and it seems correct. When post CWC drift is removed the Slavs blow the other groups, especially British Islanders out of the water with regard to closeness to steppe bronze age samples.

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    Quote Originally Posted by Cynic View Post
    Why do I think what is happening? The drift?

    ...

    When post CWC drift is removed the Slavs blow the other groups, especially British Islanders out of the water with regard to closeness to steppe bronze age samples.

    Very interesting!

    Why do you think that is? Do the British have more Farmer or other ancestry that separates them from the Slavs, in this regard?
    dosas: 56.25% Greek_Macedonia + 43.75% Greek_Trabzon @ 1.769
    wife: 50% English + 50% Irish @ 1.837
    kid1: 56.25% English + 43.75% Greek_Cappadocia @ 1.817
    kid2: 56.25% English_Cornwall + 43.75% Greek_Cappadocia @ 1.866

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    Quote Originally Posted by dosas View Post
    Very interesting!

    Why do you think that is? Do the British have more Farmer or other ancestry that separates them from the Slavs, in this regard?
    Yes that’s correct. Scandos fall in between the two groups. Difference between EHG and Yamnaya is way less than ANF and Yamnaya.

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    Quote Originally Posted by Cynic View Post
    Today I embarked on a project which was to recreate the G25 averages from northwestern, northern, and eastern Europe without drift and see how they score. It has been a mystery to a lot of people why eastern Europeans, in spite of having about as much Bronze Age steppe as NW/N Euros, do not seem to be closer to the ancient steppe groups despite their additional EHG rich ancestry and the fact that the Urheimat of Indo-Europeans was in eastern Europe. Some argued that it's because of Baltic HG ancestry which makes no sense as it can be modeled well as a mix of EHG and WHG and extremely well as a mix of Norwegian HG and WHG. The real culprit is simply post-Corded Ware drift. All of the groups originating in the northern European plain from Slavs to Celts descend from the Corded Ware culture and following its breakup, there has been a substantial bottleneck among Balto-Slavic populations which makes them act strangely on G25. While they cannot be modeled to a low fit without using Baltic_BA, you can still get reliable values for ancestral components. I used this fact to create drift-less versions of the averages for various groups.

    These are the ancients(all averages) I used to construct these ghost samples:

    Code:
    Baltic_LVA_HG,0.1292603,0.1004104,0.1802636,0.1972329,0.1064236,0.0560919,0.0083574,0.0207106,0.0524476,-0.0261394,-0.0046788,-0.0181151,0.0281434,-0.0053759,0.0355759,0.0480141,0.003072,0.0040856,-0.0059236,0.042325,0.0613526,0.0130531,-0.0262979,-0.1110549,0.0095949
    Corded_Ware_CZE,0.1235794,0.11548,0.0543053,0.0784429,0.0129254,0.0249007,0.0030886,0.0019119,-0.018641,-0.0284549,-0.002018,0.0014771,-0.0070721,-0.0185596,0.0222194,0.0103987,0.000447,0.0010679,0.004561,0.0077359,0.0002496,-0.0014663,0.0028876,0.0073159,-0.0004619
    POL_Globular_Amphora,0.1263436,0.1689961,0.0604725,-0.020045,0.0843053,-0.017849,0.0016865,0.0077916,0.0537897,0.0705682,0.0004012,0.0095386,-0.0161428,-0.0056101,-0.0098915,0.0004289,0.0045635,0.0068486,0.0062036,-0.000846,0.0091822,0.0078046,-0.013956,-0.0272541,0.0009228
    RUS_Sidelkino_HG,0.118376,0.039606,0.133501,0.195739,0.001846,0.054105,-0.019271,-0.018922,-0.0045,-0.071437,0.010068,-0.012139,0.030475,-0.043351,0.027008,0.02201,-0.002738,-0.003927,-0.008547,0.019509,-0.003868,0.011623,0.005546,-0.022413,-0.001796
    SWE_Motala_HG,0.13249,0.0895696,0.1651034,0.187341,0.0864774,0.0551646,-0.00235,0.008538,0.0376324,-0.0389258,0.0016562,-0.0187034,0.0310404,-0.0173406,0.0315686,0.049297,0.005763,0.0024324,-0.006335,0.039744,0.0507604,0.014418,-0.022086,-0.0977008,0.0070412
    And these are the resulting drift free averages:
    Code:
    Belarus_driftless,0.124628156,0.123529045,0.067746975,0.072553474,0.034793846,0.020347991,0.003355369,0.004800759,0.001218347,-0.010601869,-0.001848141,0.000992011,-0.005235566,-0.014962586,0.017812597,0.012310385,0.001436987,0.002392599,0.003825892,0.009598054,0.007827697,0.001606821,-0.00297074,-0.010437898,0.000770143
    Irish_driftless,0.124358904,0.13057154,0.05604445,0.050669312,0.033054532,0.012845285,0.002693208,0.003569975,0.001784457,-0.000530386,-0.001335786,0.003750443,-0.009630037,-0.014907841,0.013164126,0.007587216,0.001607853,0.002698057,0.005024213,0.005315804,0.002768593,0.001148094,-0.001862295,-0.00243284,-7.14146E-05
    Lith_driftless,0.124839073,0.117858264,0.077053678,0.090092077,0.036090794,0.026371879,0.003884111,0.005773163,0.000679079,-0.018739201,-0.002258896,-0.001213346,-0.001726818,-0.015022016,0.021551719,0.016081849,0.001295951,0.002142401,0.002870115,0.013016883,0.011843392,0.001960579,-0.003832346,-0.016766941,0.001438259
    Norwegian_driftless,0.124201502,0.128170687,0.058054201,0.054506914,0.032195428,0.013946594,0.002123075,0.002981256,0.001572678,-0.002440105,-0.001040903,0.003331932,-0.008581247,-0.015656013,0.013545517,0.007968869,0.001492111,0.002521944,0.004670264,0.00569056,0.002590075,0.001414248,-0.001658428,-0.002929231,-0.000117179
    RusKurk_driftless,0.1243377,0.120837629,0.06435706,0.070872647,0.02929807,0.019862149,0.001656227,0.002493207,-0.001966756,-0.012696467,-0.000903207,0.001350263,-0.005239233,-0.017131059,0.017052919,0.01107136,0.001345235,0.001991145,0.003769041,0.008309339,0.004337191,0.001570559,-0.001370226,-0.005625864,0.000126913
    RusOrel_driftless,0.124427782,0.122283278,0.063468383,0.068480215,0.030144822,0.019084201,0.001910521,0.00280201,-0.001412141,-0.01119045,-0.001024047,0.001594271,-0.005780506,-0.016704067,0.016674346,0.010832326,0.00142462,0.002108891,0.003942763,0.008082243,0.004475928,0.001506197,-0.001570563,-0.005614818,0.000156769
    Scottish_driftless,0.124397603,0.131320766,0.056130791,0.049290482,0.03405385,0.012246789,0.002673578,0.003652291,0.002798487,0.000855938,-0.001301917,0.003863304,-0.009757027,-0.014726548,0.012714574,0.007447639,0.001665484,0.002778987,0.00504721,0.005195658,0.00289365,0.001277886,-0.002098106,-0.00291682,-5.2288E-05
    Swedish_driftless,0.124514881,0.12808893,0.061376931,0.059244661,0.034741536,0.015671187,0.002972706,0.004197208,0.002449712,-0.003795289,-0.001535114,0.002614295,-0.007772152,-0.014768041,0.014843583,0.009581267,0.001583392,0.002634292,0.004507042,0.007129509,0.005153417,0.001471737,-0.002573775,-0.006465775,0.000324005
    Ukrainian_driftless,0.124663168,0.125747348,0.061632847,0.062853035,0.032458026,0.017215516,0.002489258,0.003551484,0.000187656,-0.007433293,-0.001292208,0.00214476,-0.006991438,-0.015670783,0.015724081,0.010325792,0.001631461,0.002401776,0.004330703,0.007593483,0.00492449,0.001412508,-0.002132879,-0.005891262,0.000245132
    Note:The Lithuanian and Belarusian samples still act a bit strangely, not scoring nearly as much steppe and instead a lot more EHG than the other groups. I was about to put Orcadian too but I realized they scored exactly like Scots. Both Scots and Irish could be modeled solely with GAC and CWC with no need for another neolithic or HG source.


    These are the distances between the modified averages and some ancients:

    ...

    As you can see, all of the distances are greater without the modification but this is only to be expected. However, the most glaring disparities in fit distance between drift vs no drift is among the eastern Europeans, who go from being at the top of the match list to the bottom and their distances cut by well over 50%!

    I tried something similar creating in Vahaduo new pca coordinates based on GAC, CWC, LTU_Narva and Krasnojarsk_BA (Proto-Uralic-like). I get very similar results like you here. Lithuanians and Belarusians are lower in the list because they have much more extra HG so the ratio of HG/EEF/CHG is off compared to Steppe_MLBA

    Distance to: RUS_Sintashta_MLBA
    0.02169353 Corded_Ware_DEU
    0.02986150 KAZ_Oy_Dzhaylau_MLBA
    0.03883706 Russian_Vladimir
    0.04009279 Russian_Tver
    0.04022762 Russian_Kursk
    0.04146454 Russian_Orel
    0.04659553 Russian_Voronez
    0.04698436 Russian_Smolensk
    0.04717582 Ukrainian
    0.04746097 Belarusian
    0.04749549 Lithuanian_PA
    0.04921073 Lithuanian_RA
    0.04949406 Russian_Kostroma
    0.05011706 Estonian
    0.05015263 Lithuanian_VZ
    0.05061043 Mordovian
    0.05100195 Norwegian
    0.05111005 Swedish
    0.05134365 Lithuanian_VA
    0.05451444 Lithuanian_PZ
    0.05557930 Ukrainian_B
    0.05567156 Lithuanian_SZ
    0.05787990 Dutch
    0.06061386 German_East
    0.06380243 English
    0.06710725 English_Cornwall
    0.06761779 German
    0.07428753 Russian_Pinega
    0.07787659 Corded_Ware_POL_early
    0.08879334 Swiss_German
    0.10273238 Swiss_French
    0.16606359 Saami

    Distance to: RUS_Fatyanovo_BA
    0.02805477 Corded_Ware_DEU
    0.03293144 Russian_Vladimir
    0.03333594 KAZ_Oy_Dzhaylau_MLBA
    0.03484341 Russian_Kursk
    0.03563655 Russian_Tver
    0.03584335 Russian_Orel
    0.04099162 Russian_Voronez
    0.04124641 Ukrainian
    0.04190687 Russian_Smolensk
    0.04263970 Belarusian
    0.04347291 Lithuanian_PA
    0.04483926 Norwegian
    0.04516770 Swedish
    0.04610089 Lithuanian_RA
    0.04616706 Russian_Kostroma
    0.04723189 Estonian
    0.04725772 Mordovian
    0.04726167 Lithuanian_VZ
    0.04770456 Lithuanian_VA
    0.04938469 Ukrainian_B
    0.05171762 Dutch
    0.05254179 Lithuanian_PZ
    0.05342920 Lithuanian_SZ
    0.05462755 German_East
    0.05778297 English
    0.06116114 English_Cornwall
    0.06153688 German
    0.07266620 Russian_Pinega
    0.08277915 Swiss_German
    0.08418420 Corded_Ware_POL_early
    0.09674544 Swiss_French
    0.16585641 Saami

    Distance to: KAZ_Oy_Dzhaylau_MLBA
    0.02438811 Corded_Ware_DEU
    0.04679135 Mordovian
    0.04765156 Russian_Kostroma
    0.05184432 Russian_Tver
    0.05697160 Russian_Kursk
    0.05814113 Russian_Vladimir
    0.05978731 Russian_Orel
    0.06091331 Russian_Pinega
    0.06169829 Estonian
    0.06254648 Corded_Ware_POL_early
    0.06519912 Russian_Voronez
    0.06554691 Lithuanian_RA
    0.06590148 Lithuanian_PA
    0.06638982 Russian_Smolensk
    0.06641302 Belarusian
    0.06722758 Lithuanian_VZ
    0.06786899 Ukrainian
    0.06880217 Lithuanian_VA
    0.06922127 Lithuanian_PZ
    0.07024075 Lithuanian_SZ
    0.07397079 Swedish
    0.07450656 Norwegian
    0.07486253 Ukrainian_B
    0.08155375 Dutch
    0.08510627 German_East
    0.08824147 English
    0.09154448 German
    0.09188182 English_Cornwall
    0.11138972 Swiss_German
    0.12501981 Swiss_French
    0.14144796 Saami


    Code:
    RUS_Sintashta_MLBA,0.124434,0.058458,-0.085631
    RUS_Fatyanovo_BA,0.124502,0.061229,-0.079780
    Corded_Ware_DEU,0.119984,0.051018,-0.105517
    Russian_Kostroma,0.098272,0.042247,-0.046870
    Russian_Kursk,0.127109,0.054541,-0.045684
    Russian_Orel,0.129686,0.057482,-0.044512
    Russian_Pinega,0.075720,0.021371,-0.043558
    Russian_Smolensk,0.137640,0.052707,-0.040909
    Russian_Tver,0.121069,0.046504,-0.047510
    Russian_Voronez,0.132448,0.057491,-0.039740
    Swedish,0.141203,0.069699,-0.038677
    Swiss_French,0.146463,0.127771,-0.013075
    Swiss_German,0.144091,0.116988,-0.021818
    Norwegian,0.139541,0.078097,-0.041052
    Ukrainian,0.135121,0.064065,-0.040025
    Ukrainian_B,0.132277,0.069212,-0.031669
    Belarusian,0.138277,0.049919,-0.041044
    German,0.145128,0.094251,-0.032126
    German_East,0.146907,0.083619,-0.035273
    Lithuanian_PA,0.141167,0.043361,-0.043823
    Lithuanian_PZ,0.146712,0.025284,-0.048550
    Lithuanian_RA,0.141849,0.035206,-0.045910
    Lithuanian_SZ,0.145829,0.025815,-0.045932
    Lithuanian_VA,0.143149,0.038685,-0.042100
    Lithuanian_VZ,0.145130,0.034369,-0.046815
    English,0.146039,0.090916,-0.035129
    English_Cornwall,0.148803,0.093012,-0.033520
    Dutch,0.140792,0.087257,-0.038164
    Russian_Vladimir,0.129063,0.061166,-0.047166
    Mordovian,0.092649,0.046664,-0.048054
    KAZ_Oy_Dzhaylau_MLBA,0.098977,0.045546,-0.094402
    Saami,-0.024434,-0.003091,-0.045293
    Estonian,0.132522,0.030440,-0.044872
    Baltic_LTU_Narva,0.190484,-0.160577,0.052460
    Corded_Ware_POL_early,0.105942,0.022083,-0.151961
    RUS_Krasnoyarsk_BA,-0.470719,-0.006371,0.017420
    POL_Globular_Amphora,0.174293,0.144865,0.082081

    Davidski used qpAdm to check the proportions of Steppe/EEF/HG ancestry in Europe. It more or less shows a similar pattern only that Lithuanians and West Europeans are bit higher in the list. Based on qpAdm which in the end is the method i would trust most here Steppe ancestry is more or less the same in Northwest and Northeast Europe (with maybe a peak among South-Central Russians and Ukrainians) with people in higher latitudes tending to have more Steppe ancestry except in the cases, they are very rich in Proto-Uralic/Siberian ancestry like Saami or very extremely rich in HG ancestry like some Balts.

    https://docs.google.com/spreadsheets...gid=1142599969

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     Cynic (07-28-2021)

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    Quote Originally Posted by Cynic View Post
    Today I embarked on a project which was to recreate the G25 averages from northwestern, northern, and eastern Europe without drift and see how they score. It has been a mystery to a lot of people why eastern Europeans, in spite of having about as much Bronze Age steppe as NW/N Euros, do not seem to be closer to the ancient steppe groups despite their additional EHG rich ancestry and the fact that the Urheimat of Indo-Europeans was in eastern Europe. Some argued that it's because of Baltic HG ancestry which makes no sense as it can be modeled well as a mix of EHG and WHG and extremely well as a mix of Norwegian HG and WHG. The real culprit is simply post-Corded Ware drift. All of the groups originating in the northern European plain from Slavs to Celts descend from the Corded Ware culture and following its breakup, there has been a substantial bottleneck among Balto-Slavic populations which makes them act strangely on G25. While they cannot be modeled to a low fit without using Baltic_BA, you can still get reliable values for ancestral components. I used this fact to create drift-less versions of the averages for various groups.

    These are the ancients(all averages) I used to construct these ghost samples:

    Code:
    Baltic_LVA_HG,0.1292603,0.1004104,0.1802636,0.1972329,0.1064236,0.0560919,0.0083574,0.0207106,0.0524476,-0.0261394,-0.0046788,-0.0181151,0.0281434,-0.0053759,0.0355759,0.0480141,0.003072,0.0040856,-0.0059236,0.042325,0.0613526,0.0130531,-0.0262979,-0.1110549,0.0095949
    Corded_Ware_CZE,0.1235794,0.11548,0.0543053,0.0784429,0.0129254,0.0249007,0.0030886,0.0019119,-0.018641,-0.0284549,-0.002018,0.0014771,-0.0070721,-0.0185596,0.0222194,0.0103987,0.000447,0.0010679,0.004561,0.0077359,0.0002496,-0.0014663,0.0028876,0.0073159,-0.0004619
    POL_Globular_Amphora,0.1263436,0.1689961,0.0604725,-0.020045,0.0843053,-0.017849,0.0016865,0.0077916,0.0537897,0.0705682,0.0004012,0.0095386,-0.0161428,-0.0056101,-0.0098915,0.0004289,0.0045635,0.0068486,0.0062036,-0.000846,0.0091822,0.0078046,-0.013956,-0.0272541,0.0009228
    RUS_Sidelkino_HG,0.118376,0.039606,0.133501,0.195739,0.001846,0.054105,-0.019271,-0.018922,-0.0045,-0.071437,0.010068,-0.012139,0.030475,-0.043351,0.027008,0.02201,-0.002738,-0.003927,-0.008547,0.019509,-0.003868,0.011623,0.005546,-0.022413,-0.001796
    SWE_Motala_HG,0.13249,0.0895696,0.1651034,0.187341,0.0864774,0.0551646,-0.00235,0.008538,0.0376324,-0.0389258,0.0016562,-0.0187034,0.0310404,-0.0173406,0.0315686,0.049297,0.005763,0.0024324,-0.006335,0.039744,0.0507604,0.014418,-0.022086,-0.0977008,0.0070412
    And these are the resulting drift free averages:
    Code:
    Belarus_driftless,0.124628156,0.123529045,0.067746975,0.072553474,0.034793846,0.020347991,0.003355369,0.004800759,0.001218347,-0.010601869,-0.001848141,0.000992011,-0.005235566,-0.014962586,0.017812597,0.012310385,0.001436987,0.002392599,0.003825892,0.009598054,0.007827697,0.001606821,-0.00297074,-0.010437898,0.000770143
    Irish_driftless,0.124358904,0.13057154,0.05604445,0.050669312,0.033054532,0.012845285,0.002693208,0.003569975,0.001784457,-0.000530386,-0.001335786,0.003750443,-0.009630037,-0.014907841,0.013164126,0.007587216,0.001607853,0.002698057,0.005024213,0.005315804,0.002768593,0.001148094,-0.001862295,-0.00243284,-7.14146E-05
    Lith_driftless,0.124839073,0.117858264,0.077053678,0.090092077,0.036090794,0.026371879,0.003884111,0.005773163,0.000679079,-0.018739201,-0.002258896,-0.001213346,-0.001726818,-0.015022016,0.021551719,0.016081849,0.001295951,0.002142401,0.002870115,0.013016883,0.011843392,0.001960579,-0.003832346,-0.016766941,0.001438259
    Norwegian_driftless,0.124201502,0.128170687,0.058054201,0.054506914,0.032195428,0.013946594,0.002123075,0.002981256,0.001572678,-0.002440105,-0.001040903,0.003331932,-0.008581247,-0.015656013,0.013545517,0.007968869,0.001492111,0.002521944,0.004670264,0.00569056,0.002590075,0.001414248,-0.001658428,-0.002929231,-0.000117179
    RusKurk_driftless,0.1243377,0.120837629,0.06435706,0.070872647,0.02929807,0.019862149,0.001656227,0.002493207,-0.001966756,-0.012696467,-0.000903207,0.001350263,-0.005239233,-0.017131059,0.017052919,0.01107136,0.001345235,0.001991145,0.003769041,0.008309339,0.004337191,0.001570559,-0.001370226,-0.005625864,0.000126913
    RusOrel_driftless,0.124427782,0.122283278,0.063468383,0.068480215,0.030144822,0.019084201,0.001910521,0.00280201,-0.001412141,-0.01119045,-0.001024047,0.001594271,-0.005780506,-0.016704067,0.016674346,0.010832326,0.00142462,0.002108891,0.003942763,0.008082243,0.004475928,0.001506197,-0.001570563,-0.005614818,0.000156769
    Scottish_driftless,0.124397603,0.131320766,0.056130791,0.049290482,0.03405385,0.012246789,0.002673578,0.003652291,0.002798487,0.000855938,-0.001301917,0.003863304,-0.009757027,-0.014726548,0.012714574,0.007447639,0.001665484,0.002778987,0.00504721,0.005195658,0.00289365,0.001277886,-0.002098106,-0.00291682,-5.2288E-05
    Swedish_driftless,0.124514881,0.12808893,0.061376931,0.059244661,0.034741536,0.015671187,0.002972706,0.004197208,0.002449712,-0.003795289,-0.001535114,0.002614295,-0.007772152,-0.014768041,0.014843583,0.009581267,0.001583392,0.002634292,0.004507042,0.007129509,0.005153417,0.001471737,-0.002573775,-0.006465775,0.000324005
    Ukrainian_driftless,0.124663168,0.125747348,0.061632847,0.062853035,0.032458026,0.017215516,0.002489258,0.003551484,0.000187656,-0.007433293,-0.001292208,0.00214476,-0.006991438,-0.015670783,0.015724081,0.010325792,0.001631461,0.002401776,0.004330703,0.007593483,0.00492449,0.001412508,-0.002132879,-0.005891262,0.000245132
    Note:The Lithuanian and Belarusian samples still act a bit strangely, not scoring nearly as much steppe and instead a lot more EHG than the other groups. I was about to put Orcadian too but I realized they scored exactly like Scots. Both Scots and Irish could be modeled solely with GAC and CWC with no need for another neolithic or HG source.


    These are the distances between the modified averages and some ancients:

    ....

    As you can see, all of the distances are greater without the modification but this is only to be expected. However, the most glaring disparities in fit distance between drift vs no drift is among the eastern Europeans, who go from being the furthest to the closest matches and their distances cut by well over 50%!
    East Europeans (excluding pops around the Ural) generally do not have extra EHG ancestry at least not significant one. EHG ancestry was probably already insignificant among Pre-Slavs when Slavs arrived in the early medieval period in Central Russia and regions more in the west, where Proto-Balto-Slavs and Proto-Slavs formed generally had rather WHG-rich HGs similar to Koros_HG and LTU_Narva (mainly WHG + some EHG). Most East Europeans have extra HG compared to Steppe_MLBA/CWC Late and most NW Europeans but it was rather WHG-like. Some Russians probably have some Sarmatian/Srubnaya like shift which may originate directly from the IA steppe or from forest-steppe groups speaking Finno-Ugrian languages before Balto-Slavs

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    Quote Originally Posted by Coldmountains View Post
    East Europeans (excluding pops around the Ural) generally do not have extra EHG ancestry at least not significant one. EHG ancestry was probably already insignificant among Pre-Slavs when Slavs arrived in the early medieval period in Central Russia and regions more in the west, where Proto-Balto-Slavs and Proto-Slavs formed generally had rather WHG-rich HGs similar to Koros_HG and LTU_Narva (mainly WHG + some EHG). Most East Europeans have extra HG compared to Steppe_MLBA/CWC Late and most NW Europeans but it was rather WHG-like. Some Russians probably have some Sarmatian/Srubnaya like shift which may originate directly from the IA steppe or from forest-steppe groups speaking Finno-Ugrian languages before Balto-Slavs
    You're right actually. For what it's worth though, these are the results I obtained from which I calculated the ghosts. When I had Baltic HG, Sweden Motala HG, and EHG in the same run, only the Lithuanians and Belorussians strongly preferred Baltic HG among the Easterners although the others scored Motala HG(which is very similar, but less WHG shifted) or a mix of Motala and EHG.

     
    Target: Lithuanian_PZ
    Distance: 7.4990% / 0.07498952
    73.0 Corded_Ware_CZE
    17.6 Baltic_LVA_HG
    9.4 POL_Globular_Amphora

    Target: Swedish
    Distance: 3.0147% / 0.03014727
    70.8 Corded_Ware_CZE
    24.8 POL_Globular_Amphora
    4.4 Baltic_LVA_HG

    Target: Norwegian
    Distance: 3.1383% / 0.03138251
    70.0 Corded_Ware_CZE
    27.4 POL_Globular_Amphora
    2.6 RUS_Sidelkino_HG

    Target: Russian_Kursk
    Distance: 6.1519% / 0.06151889
    72.6 Corded_Ware_CZE
    18.2 POL_Globular_Amphora
    5.2 SWE_Motala_HG
    4.0 RUS_Sidelkino_HG

    Target: Russian_Orel
    Distance: 6.1905% / 0.06190477
    72.8 Corded_Ware_CZE
    19.2 POL_Globular_Amphora
    5.2 SWE_Motala_HG
    2.8 RUS_Sidelkino_HG

    Target: Ukrainian
    Distance: 5.9592% / 0.05959171
    72.8 Corded_Ware_CZE
    21.8 POL_Globular_Amphora
    5.4 SWE_Motala_HG

    Target: Belarusian
    Distance: 6.7391% / 0.06739135
    72.4 Corded_Ware_CZE
    17.8 POL_Globular_Amphora
    9.8 Baltic_LVA_HG


    I actually wish I'd included Poles too.

    Target: Polish
    Distance: 5.4264% / 0.05426427
    70.2 Corded_Ware_CZE
    23.8 POL_Globular_Amphora
    6.0 SWE_Motala_HG

    I also just did a simple run of CWC+GAC+WHG+EHG. Everyone seems to be getting only EHG with the exception of Lithuanians. That seems to be in spite of Baltic_HG being majority WHG like. Very interesting.
     
    Target: Swedish
    Distance: 3.1334% / 0.03133401
    66.6 Corded_Ware_CZE
    28.0 POL_Globular_Amphora
    5.4 RUS_Sidelkino_HG

    Target: Belarusian
    Distance: 6.9038% / 0.06903845
    59.6 Corded_Ware_CZE
    26.2 POL_Globular_Amphora
    14.2 RUS_Sidelkino_HG

    Target: Polish
    Distance: 5.5030% / 0.05503034
    65.2 Corded_Ware_CZE
    27.6 POL_Globular_Amphora
    7.2 RUS_Sidelkino_HG

    Target: Norwegian
    Distance: 3.1383% / 0.03138251
    70.0 Corded_Ware_CZE
    27.4 POL_Globular_Amphora
    2.6 RUS_Sidelkino_HG

    Target: Ukrainian
    Distance: 5.9955% / 0.05995528
    66.8 Corded_Ware_CZE
    25.8 POL_Globular_Amphora
    7.4 RUS_Sidelkino_HG

    Target: Russian_Orel
    Distance: 6.2218% / 0.06221819
    67.6 Corded_Ware_CZE
    22.8 POL_Globular_Amphora
    9.6 RUS_Sidelkino_HG

    Target: Lithuanian_PZ
    Distance: 7.8782% / 0.07878157
    69.6 Corded_Ware_CZE
    12.2 POL_Globular_Amphora
    9.8 RUS_Sidelkino_HG
    8.4 WHG

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    Quote Originally Posted by Coldmountains View Post
    I tried something similar creating in Vahaduo new pca coordinates based on GAC, CWC, LTU_Narva and Krasnojarsk_BA (Proto-Uralic-like). I get very similar results like you here. Lithuanians and Belarusians are lower in the list because they have much more extra HG so the ratio of HG/EEF/CHG is off compared to Steppe_MLBA

     
    Distance to: RUS_Sintashta_MLBA
    0.02169353 Corded_Ware_DEU
    0.02986150 KAZ_Oy_Dzhaylau_MLBA
    0.03883706 Russian_Vladimir
    0.04009279 Russian_Tver
    0.04022762 Russian_Kursk
    0.04146454 Russian_Orel
    0.04659553 Russian_Voronez
    0.04698436 Russian_Smolensk
    0.04717582 Ukrainian
    0.04746097 Belarusian
    0.04749549 Lithuanian_PA
    0.04921073 Lithuanian_RA
    0.04949406 Russian_Kostroma
    0.05011706 Estonian
    0.05015263 Lithuanian_VZ
    0.05061043 Mordovian
    0.05100195 Norwegian
    0.05111005 Swedish
    0.05134365 Lithuanian_VA
    0.05451444 Lithuanian_PZ
    0.05557930 Ukrainian_B
    0.05567156 Lithuanian_SZ
    0.05787990 Dutch
    0.06061386 German_East
    0.06380243 English
    0.06710725 English_Cornwall
    0.06761779 German
    0.07428753 Russian_Pinega
    0.07787659 Corded_Ware_POL_early
    0.08879334 Swiss_German
    0.10273238 Swiss_French
    0.16606359 Saami

    Distance to: RUS_Fatyanovo_BA
    0.02805477 Corded_Ware_DEU
    0.03293144 Russian_Vladimir
    0.03333594 KAZ_Oy_Dzhaylau_MLBA
    0.03484341 Russian_Kursk
    0.03563655 Russian_Tver
    0.03584335 Russian_Orel
    0.04099162 Russian_Voronez
    0.04124641 Ukrainian
    0.04190687 Russian_Smolensk
    0.04263970 Belarusian
    0.04347291 Lithuanian_PA
    0.04483926 Norwegian
    0.04516770 Swedish
    0.04610089 Lithuanian_RA
    0.04616706 Russian_Kostroma
    0.04723189 Estonian
    0.04725772 Mordovian
    0.04726167 Lithuanian_VZ
    0.04770456 Lithuanian_VA
    0.04938469 Ukrainian_B
    0.05171762 Dutch
    0.05254179 Lithuanian_PZ
    0.05342920 Lithuanian_SZ
    0.05462755 German_East
    0.05778297 English
    0.06116114 English_Cornwall
    0.06153688 German
    0.07266620 Russian_Pinega
    0.08277915 Swiss_German
    0.08418420 Corded_Ware_POL_early
    0.09674544 Swiss_French
    0.16585641 Saami

    Distance to: KAZ_Oy_Dzhaylau_MLBA
    0.02438811 Corded_Ware_DEU
    0.04679135 Mordovian
    0.04765156 Russian_Kostroma
    0.05184432 Russian_Tver
    0.05697160 Russian_Kursk
    0.05814113 Russian_Vladimir
    0.05978731 Russian_Orel
    0.06091331 Russian_Pinega
    0.06169829 Estonian
    0.06254648 Corded_Ware_POL_early
    0.06519912 Russian_Voronez
    0.06554691 Lithuanian_RA
    0.06590148 Lithuanian_PA
    0.06638982 Russian_Smolensk
    0.06641302 Belarusian
    0.06722758 Lithuanian_VZ
    0.06786899 Ukrainian
    0.06880217 Lithuanian_VA
    0.06922127 Lithuanian_PZ
    0.07024075 Lithuanian_SZ
    0.07397079 Swedish
    0.07450656 Norwegian
    0.07486253 Ukrainian_B
    0.08155375 Dutch
    0.08510627 German_East
    0.08824147 English
    0.09154448 German
    0.09188182 English_Cornwall
    0.11138972 Swiss_German
    0.12501981 Swiss_French
    0.14144796 Saami


    Code:
    RUS_Sintashta_MLBA,0.124434,0.058458,-0.085631
    RUS_Fatyanovo_BA,0.124502,0.061229,-0.079780
    Corded_Ware_DEU,0.119984,0.051018,-0.105517
    Russian_Kostroma,0.098272,0.042247,-0.046870
    Russian_Kursk,0.127109,0.054541,-0.045684
    Russian_Orel,0.129686,0.057482,-0.044512
    Russian_Pinega,0.075720,0.021371,-0.043558
    Russian_Smolensk,0.137640,0.052707,-0.040909
    Russian_Tver,0.121069,0.046504,-0.047510
    Russian_Voronez,0.132448,0.057491,-0.039740
    Swedish,0.141203,0.069699,-0.038677
    Swiss_French,0.146463,0.127771,-0.013075
    Swiss_German,0.144091,0.116988,-0.021818
    Norwegian,0.139541,0.078097,-0.041052
    Ukrainian,0.135121,0.064065,-0.040025
    Ukrainian_B,0.132277,0.069212,-0.031669
    Belarusian,0.138277,0.049919,-0.041044
    German,0.145128,0.094251,-0.032126
    German_East,0.146907,0.083619,-0.035273
    Lithuanian_PA,0.141167,0.043361,-0.043823
    Lithuanian_PZ,0.146712,0.025284,-0.048550
    Lithuanian_RA,0.141849,0.035206,-0.045910
    Lithuanian_SZ,0.145829,0.025815,-0.045932
    Lithuanian_VA,0.143149,0.038685,-0.042100
    Lithuanian_VZ,0.145130,0.034369,-0.046815
    English,0.146039,0.090916,-0.035129
    English_Cornwall,0.148803,0.093012,-0.033520
    Dutch,0.140792,0.087257,-0.038164
    Russian_Vladimir,0.129063,0.061166,-0.047166
    Mordovian,0.092649,0.046664,-0.048054
    KAZ_Oy_Dzhaylau_MLBA,0.098977,0.045546,-0.094402
    Saami,-0.024434,-0.003091,-0.045293
    Estonian,0.132522,0.030440,-0.044872
    Baltic_LTU_Narva,0.190484,-0.160577,0.052460
    Corded_Ware_POL_early,0.105942,0.022083,-0.151961
    RUS_Krasnoyarsk_BA,-0.470719,-0.006371,0.017420
    POL_Globular_Amphora,0.174293,0.144865,0.082081


    Davidski used qpAdm to check the proportions of Steppe/EEF/HG ancestry in Europe. It more or less shows a similar pattern only that Lithuanians and West Europeans are bit higher in the list. Based on qpAdm which in the end is the method i would trust most here Steppe ancestry is more or less the same in Northwest and Northeast Europe (with maybe a peak among South-Central Russians and Ukrainians) with people in higher latitudes tending to have more Steppe ancestry except in the cases, they are very rich in Proto-Uralic/Siberian ancestry like Saami or very extremely rich in HG ancestry like some Balts.

    https://docs.google.com/spreadsheets...gid=1142599969
    Yep, It seems that Steppe/EEF ancestry corresponds almost to a tee with latitude, i.e., the more Northern/Southern the location of a population, the more Steppe/EEF ancestry they have.

     


     


    The proportions are broadly similar across Northern Europeans, but Eastern Europeans just about edge out NW Europeans (Granted, I don't have too many Western European pops in this dataset, I will try this run with one that has Swedes and Germans, but I doubt they have more Steppe ancestry than the Norwegians that are included here) by a very narrow margin. Balts might be a little bit lower if some WHG proxy was used instead of Barcin_N as the third pop but East-Slavs would still probably be the most Steppe-shifted populations.

    This is me speculating, but I suspect that as East Slavs expanded into Russia, they gobbled up Uralic-speakers that would have harbored substantial Steppe-MLBA ancestry. For example, Mordvins are very heavily admixed with Balto-Slavs but can still be modeled as 25% Steppe-MLBA; presumably, there were similar populations around Central Russia 1000+ years ago (afaik there were plenty of Mordvin villages in places like Nizhny Novgorod that were Russified rather recently), being relatively low on Kra001/Uralic admixture and with significant Steppe ancestry.
    YDNA (P): R-Y33
    YDNA (P, maternal line): R-Y20756
    YDNA(M): E-Y6938

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  18. #10
    Moderator
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    Y-DNA (P)
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    Quote Originally Posted by Cynic View Post
    You're right actually. For what it's worth though, these are the results I obtained from which I calculated the ghosts. When I had Baltic HG, Sweden Motala HG, and EHG in the same run, only the Lithuanians and Belorussians strongly preferred Baltic HG among the Easterners although the others scored Motala HG(which is very similar, but less WHG shifted) or a mix of Motala and EHG.

     
    Target: Lithuanian_PZ
    Distance: 7.4990% / 0.07498952
    73.0 Corded_Ware_CZE
    17.6 Baltic_LVA_HG
    9.4 POL_Globular_Amphora

    Target: Swedish
    Distance: 3.0147% / 0.03014727
    70.8 Corded_Ware_CZE
    24.8 POL_Globular_Amphora
    4.4 Baltic_LVA_HG

    Target: Norwegian
    Distance: 3.1383% / 0.03138251
    70.0 Corded_Ware_CZE
    27.4 POL_Globular_Amphora
    2.6 RUS_Sidelkino_HG

    Target: Russian_Kursk
    Distance: 6.1519% / 0.06151889
    72.6 Corded_Ware_CZE
    18.2 POL_Globular_Amphora
    5.2 SWE_Motala_HG
    4.0 RUS_Sidelkino_HG

    Target: Russian_Orel
    Distance: 6.1905% / 0.06190477
    72.8 Corded_Ware_CZE
    19.2 POL_Globular_Amphora
    5.2 SWE_Motala_HG
    2.8 RUS_Sidelkino_HG

    Target: Ukrainian
    Distance: 5.9592% / 0.05959171
    72.8 Corded_Ware_CZE
    21.8 POL_Globular_Amphora
    5.4 SWE_Motala_HG

    Target: Belarusian
    Distance: 6.7391% / 0.06739135
    72.4 Corded_Ware_CZE
    17.8 POL_Globular_Amphora
    9.8 Baltic_LVA_HG


    I actually wish I'd included Poles too.

    Target: Polish
    Distance: 5.4264% / 0.05426427
    70.2 Corded_Ware_CZE
    23.8 POL_Globular_Amphora
    6.0 SWE_Motala_HG

    I also just did a simple run of CWC+GAC+WHG+EHG. Everyone seems to be getting only EHG with the exception of Lithuanians. That seems to be in spite of Baltic_HG being majority WHG like. Very interesting.
     
    Target: Swedish
    Distance: 3.1334% / 0.03133401
    66.6 Corded_Ware_CZE
    28.0 POL_Globular_Amphora
    5.4 RUS_Sidelkino_HG

    Target: Belarusian
    Distance: 6.9038% / 0.06903845
    59.6 Corded_Ware_CZE
    26.2 POL_Globular_Amphora
    14.2 RUS_Sidelkino_HG

    Target: Polish
    Distance: 5.5030% / 0.05503034
    65.2 Corded_Ware_CZE
    27.6 POL_Globular_Amphora
    7.2 RUS_Sidelkino_HG

    Target: Norwegian
    Distance: 3.1383% / 0.03138251
    70.0 Corded_Ware_CZE
    27.4 POL_Globular_Amphora
    2.6 RUS_Sidelkino_HG

    Target: Ukrainian
    Distance: 5.9955% / 0.05995528
    66.8 Corded_Ware_CZE
    25.8 POL_Globular_Amphora
    7.4 RUS_Sidelkino_HG

    Target: Russian_Orel
    Distance: 6.2218% / 0.06221819
    67.6 Corded_Ware_CZE
    22.8 POL_Globular_Amphora
    9.6 RUS_Sidelkino_HG

    Target: Lithuanian_PZ
    Distance: 7.8782% / 0.07878157
    69.6 Corded_Ware_CZE
    12.2 POL_Globular_Amphora
    9.8 RUS_Sidelkino_HG
    8.4 WHG
    The EHG, which many East Europeans get in Global25 models, has rather something to do with overfitting and does not show up in qpAdm which is so far the only method that really can differentiate between direct genetic contribution and indirect one like in this case (EHG via Steppe groups). Davidski made a blog post about this https://eurogenes.blogspot.com/2020/...n-present.html, Even Saami seem not to have significant direct EHG ancestry in qpAdm and rather some WHG-rich HG ancestry on top of their Corded Ware-like and Kra_BA-like ancestry

    Polish
    HUN_Koros_N_HG 0.127
    RUS_Karelia_HG 0.000
    TUR_Barcin_N 0.321
    UKR_Yamnaya 0.552
    chisq 7.554
    tail prob 0.478197

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