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Thread: UMAP of (sub)modern Europeans

  1. #1
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    UMAP of (sub)modern Europeans

    To better get a global picture, I prepared an UMAP plot of the (sub)modern Europeans in Global25, including the recent VK2020.
    UMAP1.2.png
    The plot shows 3 large and 2 small clusters. I have marked the VK2020 samples with a red V.
    The large cluster on the left are the Western samples.
    The upper cluster consists of East-European and North-East European samples.
    The third cluster represents South-Eastern/EastMed samples, including a Balkan offshoot with a single V.
    The small cluster at the bottom are 11 Sardinians and 4 Sardinian-like submodern samples and 1 ITA_Rome_Late_Antiquity.
    The small cluster on the right consists of 20 Sarmatians, 5 Cimmerians, 1 RUS_Nomad_MA and 2 Scythians.
    Of the 53 VK2020 samples in the upper East/North-East cluster nearly half (24/53) are VK2020_SWE_Gotland_VA. Only 18 Gottland samples are located outside this cluster.

    The next plot shows another UMAP.
    The West-European samples have been spread like an unrolled parchment.
    This plot suggests that the European samples near the left border are partitioned into three clusters.
    The upper blob has relatively the most VK2020 samples, but I do not see an attraction for specific groups.
    The middle blob has an attraction for modern Icelandic 10/12 and England_Saxon 6/8.
    The lower blob appears even less specific but has some attraction for DEU_MA 6/10 and VK2020_GreenlandE_VA 6/11.
    I am not yet convinced of the validity of this partition.
    UMAP2.3.png

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  3. #2
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    Thank you!.
    Maybe to write a few words what is UMAP actually:

    UMAP (Uniform Manifold Approximation and Projection) is a novel manifold learning technique for dimension reduction. UMAP is constructed from a theoretical framework based in Riemannian geometry and algebraic topology. The result is a practical scalable algorithm that applies to real world data. The UMAP algorithm is competitive with t-SNE for visualization quality, and arguably preserves more of the global structure with superior run time performance. Furthermore, UMAP has no computational restrictions on embedding dimension, making it viable as a general purpose dimension reduction technique for machine learning.

     
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    Quote Originally Posted by ph2ter View Post
    Thank you!.
    Maybe to write a few words what is UMAP actually:

    UMAP (Uniform Manifold Approximation and Projection) is a novel manifold learning technique for dimension reduction. UMAP is constructed from a theoretical framework based in Riemannian geometry and algebraic topology. The result is a practical scalable algorithm that applies to real world data. The UMAP algorithm is competitive with t-SNE for visualization quality, and arguably preserves more of the global structure with superior run time performance. Furthermore, UMAP has no computational restrictions on embedding dimension, making it viable as a general purpose dimension reduction technique for machine learning.

    For the less mathematical among the members: UMAP is the Rolls-Royce of the two-dimensions scatterplots (according to its proponents).

    A few words about applying UMAP to the Global25 PCA:
    UMAP is usually applied to much larger datasets. In that case the workflow starts with a PCA to speed up the calculations (it might take days!).
    As the Global25 data are itself PCA data, I think it is quite legitimate to apply UMAP on the Global25 data.

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    My first UMAP:

     
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    Quote Originally Posted by ph2ter View Post
    My first UMAP:
    Nice.
    I had excluded Turkish/Caucasus and the far North-East of European Russia.
    For the number of nearest neighbors I used the standard 15; how many did you use?

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    Quote Originally Posted by Huijbregts View Post
    Nice.
    I had excluded Turkish/Caucasus and the far North-East of European Russia.
    For the number of nearest neighbors I used the standard 15; how many did you use?
    I tried with 15, but the structure did not correspond with the map of Europe well, so I changed it to 50, a then the plot turned out much better.

    And I have the whole world, but in the picture above I have only a segment of it.
    Last edited by ph2ter; 10-11-2020 at 03:23 PM.
     
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    And my family adopts DNK_Langeland_VA:VK274
     
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    I ran a UMAP on the Dutch members:
    UMAP3.2.png
    H=Huijbregts, R=Radboud, F=Finn, FD=Fin_dad, FM=Finn_mom,
    M=miremont, K=Kellebel, KD=Kellebel_dad, KM=Kellebel_mom, KG=Kellebelgram

    I also calculated the 9 closest neighbors for the Dutch members:
    Huijbregts:
    [1] "Welsh:WalesL42" "English:HG02215" "VK2020_SWE_Skara_VA:VK398"
    [4] "VK2020_SWE_Skara_VA:VK31" "French_Brittany:Rennes_B_98" "VK2020_England_Oxford_VA:VK176"
    [7] "English_Cornwall:HG00235" "French_Brittany:Rennes_B_6" "Welsh:WalesDR84"

    Radboud:
    [1] "VK2020_RUS_Ladoga_VA:VK15" "English_Cornwall:HG00249"
    [3] "Norwegian:NOR109" "VK2020_England_Dorset_VA:VK258"
    [5] "ISL_Viking_Age_Early_Christian:TSK-A-26" "VK2020_SWE_Skara_VA:VK34"
    [7] "Norwegian:NOR106" "VK2020_England_Oxford_VA:VK147"
    [9] "Welsh:WalesCHF12"

    Finn:
    [1] "FinnMom" "FinnDad" "VK2020_DNK_Langeland_VA:VK290"
    [4] "Swedish:Sweden7" "Swedish:Sweden9" "VK2020_England_Oxford_VA:VK172"
    [7] "VK2020_DNK_Funen_VA:VK316" "VK2020_DNK_Funen_VA:VK373" "VK2020_SWE_Gotland_VA:VK58"

    Finn_dad
    [1] "Finn" "Welsh:WalesDR94" "Swedish:Sweden9"
    [4] "English:England11" "VK2020_RUS_Ladoga_VA:VK219" "Swedish:Sweden4"
    [7] "England_Saxon:I0774" "Norwegian:NOR108" "VK2020_SWE_Skara_VA:VK40"

    Finn_mom
    [1] "Finn" "VK2020_DNK_Langeland_VA:VK290" "Swedish:Sweden7"
    [4] "Swedish:Sweden9" "VK2020_England_Oxford_VA:VK173" "VK2020_EST_Saaremaa_EVA:VK496"
    [7] "FinnDad" "ITA_Collegno_MA:CL84" "Scottish:Scottish5"

    miremont
    [1] "Icelandic:NA15757" "Welsh:WalesL40"
    [3] "French_Brittany:Rennes_B_59" "Danishenmark2"
    [5] "Welsh:WalesL86" "Orcadian:HGDP00800"
    [7] "HUN_MA_Szolad:SZ42" "English_Cornwall:HG00259"
    [9] "SWE_Viking_Age_Sigtuna:vik_grt035"

    Kellebel_dad
    [1] "VK2020_ISL_Hofstadir_VA:VK123" "English:English2" "England_Saxon:I0774"
    [4] "Belgian:Belgium23" "Scottish:Scottish24" "VK2020_SWE_Gotland_VA:VK468"
    [7] "English_Cornwall:HG00259" "English_Cornwall:HG00232" "FinnDad"

    # Kellebel_gram
    [1] "Kel_mom" "French_Pas-de-Calais:French23862"
    [3] "French_Nord:N_19" "Kellebel"
    [5] "Welsh:WalesL40" "English:HG01790"
    [7] "Swiss_German:Swiss_German5" "Belgian:Belgium13"
    [9] "English_Cornwall:HG00255"

    # Kellebel_mom
    [1] "Kellebel" "Kel_gram" "French_Nord:N_52"
    [4] "French_Nord:N_19" "French_Occitanie:T_67" "French_Nord:N_21_2"
    [7] "French_Alsace:A_79" "ITA_Rome_Renaissance:RMPR1220" "Welsh:WalesL40"

    # Kellebel
    [1] "Welsh:WalesL40" "Kel_mom" "French_Brittany:Rennes_B_46"
    [4] "English_Cornwall:HG00255" "French_Brittany:Rennes_B_23" "English_Cornwall:HG00264"
    [7] "Kel_gram" "French_Brittany:Rennes_B_32" "French_Brittany:French24090"

    Keep in mind that this is a result of a model, which as never perfect.
    But it is one of the best in the field and IMO the result looks plausible.

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  17. #9
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    Quote Originally Posted by Huijbregts View Post
    I ran a UMAP on the Dutch members:
    UMAP3.2.png
    H=Huijbregts, R=Radboud, F=Finn, FD=Fin_dad, FM=Finn_mom,
    M=miremont, K=Kellebel, KD=Kellebel_dad, KM=Kellebel_mom, KG=Kellebelgram

    I also calculated the 9 closest neighbors for the Dutch members:
    Huijbregts:
    [1] "Welsh:WalesL42" "English:HG02215" "VK2020_SWE_Skara_VA:VK398"
    [4] "VK2020_SWE_Skara_VA:VK31" "French_Brittany:Rennes_B_98" "VK2020_England_Oxford_VA:VK176"
    [7] "English_Cornwall:HG00235" "French_Brittany:Rennes_B_6" "Welsh:WalesDR84"

    Radboud:
    [1] "VK2020_RUS_Ladoga_VA:VK15" "English_Cornwall:HG00249"
    [3] "Norwegian:NOR109" "VK2020_England_Dorset_VA:VK258"
    [5] "ISL_Viking_Age_Early_Christian:TSK-A-26" "VK2020_SWE_Skara_VA:VK34"
    [7] "Norwegian:NOR106" "VK2020_England_Oxford_VA:VK147"
    [9] "Welsh:WalesCHF12"

    Finn:
    [1] "FinnMom" "FinnDad" "VK2020_DNK_Langeland_VA:VK290"
    [4] "Swedish:Sweden7" "Swedish:Sweden9" "VK2020_England_Oxford_VA:VK172"
    [7] "VK2020_DNK_Funen_VA:VK316" "VK2020_DNK_Funen_VA:VK373" "VK2020_SWE_Gotland_VA:VK58"

    Finn_dad
    [1] "Finn" "Welsh:WalesDR94" "Swedish:Sweden9"
    [4] "English:England11" "VK2020_RUS_Ladoga_VA:VK219" "Swedish:Sweden4"
    [7] "England_Saxon:I0774" "Norwegian:NOR108" "VK2020_SWE_Skara_VA:VK40"

    Finn_mom
    [1] "Finn" "VK2020_DNK_Langeland_VA:VK290" "Swedish:Sweden7"
    [4] "Swedish:Sweden9" "VK2020_England_Oxford_VA:VK173" "VK2020_EST_Saaremaa_EVA:VK496"
    [7] "FinnDad" "ITA_Collegno_MA:CL84" "Scottish:Scottish5"

    miremont
    [1] "Icelandic:NA15757" "Welsh:WalesL40"
    [3] "French_Brittany:Rennes_B_59" "Danishenmark2"
    [5] "Welsh:WalesL86" "Orcadian:HGDP00800"
    [7] "HUN_MA_Szolad:SZ42" "English_Cornwall:HG00259"
    [9] "SWE_Viking_Age_Sigtuna:vik_grt035"

    Kellebel_dad
    [1] "VK2020_ISL_Hofstadir_VA:VK123" "English:English2" "England_Saxon:I0774"
    [4] "Belgian:Belgium23" "Scottish:Scottish24" "VK2020_SWE_Gotland_VA:VK468"
    [7] "English_Cornwall:HG00259" "English_Cornwall:HG00232" "FinnDad"

    # Kellebel_gram
    [1] "Kel_mom" "French_Pas-de-Calais:French23862"
    [3] "French_Nord:N_19" "Kellebel"
    [5] "Welsh:WalesL40" "English:HG01790"
    [7] "Swiss_German:Swiss_German5" "Belgian:Belgium13"
    [9] "English_Cornwall:HG00255"

    # Kellebel_mom
    [1] "Kellebel" "Kel_gram" "French_Nord:N_52"
    [4] "French_Nord:N_19" "French_Occitanie:T_67" "French_Nord:N_21_2"
    [7] "French_Alsace:A_79" "ITA_Rome_Renaissance:RMPR1220" "Welsh:WalesL40"

    # Kellebel
    [1] "Welsh:WalesL40" "Kel_mom" "French_Brittany:Rennes_B_46"
    [4] "English_Cornwall:HG00255" "French_Brittany:Rennes_B_23" "English_Cornwall:HG00264"
    [7] "Kel_gram" "French_Brittany:Rennes_B_32" "French_Brittany:French24090"

    Keep in mind that this is a result of a model, which as never perfect.
    But it is one of the best in the field and IMO the result looks plausible.
    Thanks Huijbregts, of course I have a lot of curios questions....but I keep my mouth shut, because these things sets my associative thoughts in action

    The combination (and explanation) with this one:
    'The next plot shows another UMAP.
    The West-European samples have been spread like an unrolled parchment.
    This plot suggests that the European samples near the left border are partitioned into three clusters.
    The upper blob has relatively the most VK2020 samples, but I do not see an attraction for specific groups.
    The middle blob has an attraction for modern Icelandic 10/12 and England_Saxon 6/8.
    The lower blob appears even less specific but has some attraction for DEU_MA 6/10 and VK2020_GreenlandE_VA 6/11.'

    Would be fascinating....nevertheless

    So: ok nice outcomes.

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    Quote Originally Posted by Finn View Post
    Thanks Huijbregts, of course I have a lot of curios questions....but I keep my mouth shut, because these things sets my associative thoughts in action

    The combination (and explanation) with this one:
    'The next plot shows another UMAP.
    The West-European samples have been spread like an unrolled parchment.
    This plot suggests that the European samples near the left border are partitioned into three clusters.
    The upper blob has relatively the most VK2020 samples, but I do not see an attraction for specific groups.
    The middle blob has an attraction for modern Icelandic 10/12 and England_Saxon 6/8.
    The lower blob appears even less specific but has some attraction for DEU_MA 6/10 and VK2020_GreenlandE_VA 6/11.'

    Would be fascinating....nevertheless

    So: ok nice outcomes.

    I will try to zoom in on the West-Europeans.
    By the way, did you notice that Sweden9 is a near neighbor for all three of you? Moreover you share Sweden7 with your mother.

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