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Thread: Davidski's Global 25 nMonte results

  1. #21
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    R1a > M198 > YP 1337

    Poland
    Quote Originally Posted by Tomenable View Post
    My PCA values:

    Code:
    ,PC1,PC2,PC3,PC4,PC5,PC6,PC7,PC8,PC9,PC10,PC11,PC12,PC13,PC14,PC15,PC16,PC17,PC18,PC19,PC20,PC21,PC22,PC23,PC24,PC25 
    Tomenable,0.0117,0.0137,0.0175,0.018,0.0109,0.0081,0.0028,0.0042,0.0003,-0.01,-0.0024,-0.0011,0.0068,0.0063,-0.0056,-0.0001,0.0023,0.0014,-0.0006,-0.0012,-0.0079,-0.0006,0.0053,0.005,-0.0026
    Code:
    [1] "1. CLOSEST SINGLE ITEM DISTANCE%"
               Czech        Hungarian        Slovakian        Ukrainian 
            1.341786         1.468472         1.482861         1.514171 
            Croatian           Polish           German Russian_Kostroma 
            1.555347         1.561174         1.746808         1.751163

    nMonte3

    [1] "distance%=0.9402"

    Tomenable

    Czech,26.4
    Slovakian,20
    Hungarian,13.2
    Russian_Kostroma,9.2
    Russian_Tver,4.8
    Cossack_Ukrainian,3.6
    Russian_Kursk,3.2
    Serbian,2.4
    Ukrainian,2
    Belarusian,1.8
    Ingrian,1.8
    Macedonian,1.6
    Russian_Orel,1.4
    Slav_Bohemia,1.2
    Poltavka_outlier,0.8
    Komi,0.6
    Lithuanian,0.6
    Poltavka,0.6
    Sintashta,0.6
    Andronovo,0.4
    Karasuk,0.4
    Potapovka,0.4
    Scythian_AldyBel,0.4
    Alberstedt_LN,0.2
    Chuvash,0.2
    Ireland_EBA,0.2
    Mansi,0.2
    Mari,0.2
    Norwegian,0.2
    Romanian,0.2
    Samara_Eneolithic,0.2
    San,0.2
    Sarmatian_Pokrovka,0.2
    Srubnaya,0.2
    Srubnaya_outlier,0.2
    Tatar,0.2


    nMonte2

    [1] "distance%=0.7722 / distance=0.007722"

    Tomenable

    Russian_Tver 28.70
    Lithuanian 21.25
    LBKT_MN 10.90
    Srubnaya_outlier 9.00

    Belarusian 5.65
    Alberstedt_LN 5.15
    Norwegian 5.05
    Serbian 4.45
    Poltavka_outlier 3.70
    CWC_Baltic_early 2.20
    Slovakian 2.20
    Mari 0.90
    South_Africa_2000BP 0.40
    South_Africa_1300BP 0.25
    Boncuklu_N 0.15
    Masai 0.05


    restricted

    [1] "distance%=0.7861 / distance=0.007861"

    Tomenable

    Russian_Tver 36.90
    Belarusian 19.55
    LBKT_MN 9.40
    Alberstedt_LN 8.80
    Srubnaya_outlier 8.45
    Norwegian 6.70
    Lithuanian 5.00
    Poltavka_outlier 2.45
    Serbian 2.45
    CWC_Baltic_early 0.30



    nMonte1


    [1] "distance%=0.7725 / distance=0.007725"

    Tomenable

    Russian_Tver 28.60
    Lithuanian 21.90
    LBKT_MN 10.35
    Srubnaya_outlier 8.95

    Alberstedt_LN 5.50
    Serbian 5.10
    Norwegian 5.05
    Belarusian 4.35
    Poltavka_outlier 3.20
    Slovakian 2.55
    CWC_Baltic_early 2.30
    Mari 1.00
    South_Africa_2000BP 0.40
    Boncuklu_N 0.35
    South_Africa_1300BP 0.25
    Greece_Peloponnese_N 0.10
    Masai 0.05
    Last edited by lukaszM; 02-12-2018 at 01:18 PM.

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  3. #22
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    Poland
    In your case nMonte3 is more probable because is more western shifted and more inline with single distances (there were always the same of course).
    Last edited by lukaszM; 02-12-2018 at 01:14 PM.

  4. #23
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    R1a > M198 > YP 1337

    Poland
    ............
    Last edited by lukaszM; 02-12-2018 at 02:17 PM.

  5. #24
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    I'd say that mixing many modern and ancient samples in models is a bad idea, unless there are absolutely no ancient samples available to cover some types of ancestry, like ASI.

    Also using many, very similar reference samples is likely to result in massive overfitting. So also a bad idea.

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  7. #25
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    R1a > M198 > YP 1337

    Poland
    Quote Originally Posted by Generalissimo View Post
    I'd say that mixing many modern and ancient samples in models is a bad idea, unless there are absolutely no ancient samples available to cover some types of ancestry, like ASI.

    Also using many, very similar reference samples is likely to result in massive overfitting. So also a bad idea.
    I used spreadsheet as it was. But still interesting that some ancients can show up in results besides many moderns.

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  9. #26
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    R-Z198 (DF27)
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    T2B-T152C

    Canada England Scotland Germany Poland France
    I'm in!

    ,PC1,PC2,PC3,PC4,PC5,PC6,PC7,PC8,PC9,PC10,PC11,PC1 2,PC13,PC14,PC15,PC16,PC17,PC18,PC19,PC20,PC21,PC2 2,PC23,PC24,PC25
    Sktibo,0.0119,0.0118,0.0172,0.013,0.0127,0.0044,0. 0004,0,0.0026,0.0053,-0.0026,0.0078,-0.0102,-0.0014,0.0089,0.0024,-0.0022,0.0027,0.0043,0.005,0.0036,0.0091,-0.0021,0.0064,0.0027
    Paper trail ancestry to the best of my knowledge:
    English (possibly containing some Welsh ancestry) 31.25%, Eastern European and Eastern German (Galicia, Poland) 25%, Scottish 17.96%, Scotch-Irish 12.5%, French 8.2%, Native American 1.95%, and Colonial American, 3.125%, which cannot be determined with complete certainty: there is Dutch (at least 1.36%) and some English. The rest could include Spanish, Norwegian, German, and French, but these percentages would be minuscule.

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  11. #27
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    R1a > M198 > YP 1337

    Poland
    I can do only full spreadsheet.
    Somebody can edit and make spreadsheet only with ancients because it is too much work for me (there are mixed with moderns).
    I don't have time.

    Code:
    [1] "1. CLOSEST SINGLE ITEM DISTANCES"
                English            Austrian       England_Roman            Scottish 
             0.01395759          0.01533413          0.01697973          0.01709968 
               Orcadian         French_East             Swedish Bell_Beaker_Germany 
             0.01752843          0.01806387          0.01810463          0.01818402
    [1] "distance%=1.1245"

    Sktibo

    English,60.6
    Austrian,7.2
    Swedish,7
    Bell_Beaker_Germany,3.6
    Nordic_IA,2.2
    Italian_Bergamo,1.6
    Spanish_Castilla_la_Mancha,1.4
    England_Roman,1.2
    Nordic_LN,1.2
    Basque_Spanish,0.8
    Czech,0.8
    Norwegian,0.8
    Sweden_EN,0.8
    Basque_French,0.6
    Slovakian,0.6
    Bosnian,0.4
    Greece_Peloponnese_N,0.4
    Hungarian,0.4
    Hungary_BA,0.4
    Iberia_BA,0.4
    Ireland_MN,0.4
    Italian_Tuscan,0.4
    Juang,0.4
    Moldovan,0.4
    Mycenaean,0.4
    Portugal_MBA,0.4
    Slovenian,0.4
    Albanian,0.2
    Altaian,0.2
    Baden_LCA,0.2
    Bolivian_Pando,0.2
    Boncuklu_N,0.2
    Dolgan,0.2
    French_South,0.2
    Germany_MN,0.2
    Greek,0.2
    Iberia_MN,0.2
    Karitiana,0.2
    Koros_EN,0.2
    Kumyk,0.2
    Macedonian,0.2
    Malayan,0.2
    Romanian,0.2
    Scottish,0.2
    Sicilian_East,0.2
    Spain_LNCA,0.2
    Surui,0.2
    Sweden_MN,0.2
    Tepecik_Ciftlik_N,0.2
    Tisza_LN,0.2
    Wichi,0.2

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  13. #28
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    Quote Originally Posted by lukaszM View Post
    I can do only full spreadsheet.
    Somebody can edit and make spreadsheet only with ancients because it is too much work for me (there are mixed with moderns).
    I don't have time.

    Code:
    [1] "1. CLOSEST SINGLE ITEM DISTANCES"
                English            Austrian       England_Roman            Scottish 
             0.01395759          0.01533413          0.01697973          0.01709968 
               Orcadian         French_East             Swedish Bell_Beaker_Germany 
             0.01752843          0.01806387          0.01810463          0.01818402
    [1] "distance%=1.1245"

    Sktibo

    English,60.6
    Austrian,7.2
    Swedish,7
    Bell_Beaker_Germany,3.6
    Nordic_IA,2.2
    Italian_Bergamo,1.6
    Spanish_Castilla_la_Mancha,1.4
    England_Roman,1.2
    Nordic_LN,1.2
    Basque_Spanish,0.8
    Czech,0.8
    Norwegian,0.8
    Sweden_EN,0.8
    Basque_French,0.6
    Slovakian,0.6
    Bosnian,0.4
    Greece_Peloponnese_N,0.4
    Hungarian,0.4
    Hungary_BA,0.4
    Iberia_BA,0.4
    Ireland_MN,0.4
    Italian_Tuscan,0.4
    Juang,0.4
    Moldovan,0.4
    Mycenaean,0.4
    Portugal_MBA,0.4
    Slovenian,0.4
    Albanian,0.2
    Altaian,0.2
    Baden_LCA,0.2
    Bolivian_Pando,0.2
    Boncuklu_N,0.2
    Dolgan,0.2
    French_South,0.2
    Germany_MN,0.2
    Greek,0.2
    Iberia_MN,0.2
    Karitiana,0.2
    Koros_EN,0.2
    Kumyk,0.2
    Macedonian,0.2
    Malayan,0.2
    Romanian,0.2
    Scottish,0.2
    Sicilian_East,0.2
    Spain_LNCA,0.2
    Surui,0.2
    Sweden_MN,0.2
    Tepecik_Ciftlik_N,0.2
    Tisza_LN,0.2
    Wichi,0.2
    Thanks Lucas, looks solid to me. I ran nMonte2 for myself as well:

    [1] "1. CLOSEST SINGLE ITEM DISTANCES"
    English:ENG003 Orcadian:HGDP00804 Swedish:Sweden7 England_Roman:3DT16
    0.01207932 0.01670808 0.01693960 0.01712075
    Swedish:Sweden13 Swedish:Sweden4 Swedish:Sweden9 Swedish:Sweden5
    0.01772315 0.01834067 0.01857068 0.01874620

    ST

    Swedish:Sweden16 12.45
    Icelandic:NA15755 10.95
    Scottish:Scottish6 9.25
    Swedish:Sweden5 8.05
    CWC_Germany:I1540 6.25
    LBK_EN:I0046 6.20
    Norwegian:NOR108 5.50
    English:English1 4.40
    LBK_EN:I0054 4.15
    Bell_Beaker_Germany:RISE563 3.95
    Ireland_EBA:Rathlin1 3.65
    Nordic_IA:RISE174 3.65
    English:English3 2.50
    CHG:KK1 2.20
    Srubnaya:I0235 1.70
    Icelandic:NA15766 1.65
    Swedish:Sweden2 1.55
    Yakut:785_A 1.15
    Quechua:NA11199 1.10
    Iberia_EN:I0413 1.00

    Restricted:

    ST

    Icelandic:NA15755 22.45
    Swedish:Sweden16 20.90
    LBK_EN:I0046 12.20
    Swedish:Sweden5 11.35
    CWC_Germany:I1540 8.25
    Ireland_EBA:Rathlin1 6.70
    Bell_Beaker_Germany:RISE563 4.65
    CHG:KK1 2.65
    Iberia_EN:I0413 2.65
    Nordic_IA:RISE174 2.40
    Yakut:785_A 2.40
    English:English1 1.60
    Quechua:NA11199 1.40
    Scottish:Scottish6 0.40


    It looks like nMonte 3 does it better for myself
    Last edited by sktibo; 02-13-2018 at 03:46 AM.
    Paper trail ancestry to the best of my knowledge:
    English (possibly containing some Welsh ancestry) 31.25%, Eastern European and Eastern German (Galicia, Poland) 25%, Scottish 17.96%, Scotch-Irish 12.5%, French 8.2%, Native American 1.95%, and Colonial American, 3.125%, which cannot be determined with complete certainty: there is Dutch (at least 1.36%) and some English. The rest could include Spanish, Norwegian, German, and French, but these percentages would be minuscule.

  14. #29
    Quote Originally Posted by Generalissimo View Post
    I'd say that mixing many modern and ancient samples in models is a bad idea, unless there are absolutely no ancient samples available to cover some types of ancestry, like ASI.

    Also using many, very similar reference samples is likely to result in massive overfitting. So also a bad idea.
    Well said!

  15. #30
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    Here's the official Global 25 graphic.

    Global_25_graphic.png

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