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Thread: HarappaWorld PCAs

  1. #1
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    HarappaWorld PCAs

    Here is a very preliminary PCA using HarappaWorld calculator's spreadsheet. I have also added a couple of forum members(based on their scores posted on this really old thread from 2015) just to see where some people fit in. Note this does not use the mother-of-all data Khana has put together. This is just a baby first step. If it is useful, I might create a 3D version for it, but it already does account for 93% of the variance.

    Purple=IA/IE speakers
    Green=Dravidian speakers
    Orange=AA speakers
    Forum members are Red pluses.

    Revision 3: added Kush, Xehanort, Gyanwali, and Mingle. Also, fixed color coding issue where Srilankan and Goan were darkgreen instead of purple.

    Biplot (no changes)
    harappa_biplot.png
    https://i.imgur.com/QvDToho.png

    Overall
    harappa.png
    https://i.imgur.com/vK14zfG.png

    Zoomed into members

    https://i.imgur.com/haWx2jz.png

    Version 2
     

    Revision Version 2 - added Reza family and Jortita, also added 95% ellipse
    Note that the graph has flipped... it sort of looks like a scorpio!

    Biplot - same as before
    Attachment 21143
    https://i.imgur.com/dV9qoB1.png

    Overview
    Attachment 21145
    https://i.imgur.com/lidsYCL.png

    Members zoomed in
    Attachment 21144



    Version 1:
     

    Using the biplot, we can see that the 1st quadrant has SouthIndian component, 2nd quadrant has Baloch component, 3rd quadrant has Caucasian+NE-European+NE-Asian+SW-Asian, while the 4th quadrant has Papuan+SE-Asian pull.



    Here are just the IA/Dravidian groups zoomed in.


    Last edited by poi; 02-02-2018 at 06:03 AM. Reason: Added revision 3

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  3. #2
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    Can you please plot me as well, even though it is an outdated calculator

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    Quote Originally Posted by poi View Post
    Here is a very preliminary PCA using HarappaWorld calculator's spreadsheet. I have also added a couple of forum members(based on their scores posted on this really old thread from 2015) just to see where some people fit in. Note this does not use the mother-of-all data Khana has put together. This is just a baby first step. If it is useful, I might create a 3D version for it, but it already does account for 93% of the variance.

    Purple=IA/IE speakers
    Green=Dravidian speakers
    Orange=AA speakers
    Forum members are Red pluses.

    Using the biplot, we can see that the 1st quadrant has SouthIndian component, 2nd quadrant has Baloch component, 3rd quadrant has Caucasian+NE-European+NE-Asian+SW-Asian, while the 4th quadrant has Papuan+SE-Asian pull.

    Here are just the IA/Dravidian groups zoomed in.
    I dont get how Baloch doesnt angle along with SW Asian Siberian NE Euro Caucasian

    Siberian must be a part of that grouping due to ANE

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    Clustering right between kashmiri and punjabi brahmins, makes me wonder if we really split from Brahmins.

    I'm Punjabi Ramgarhia btw.
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    @jortita @reza -- updated the PCAs and added your scores.

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    Quote Originally Posted by bmoney View Post
    I dont get how Baloch doesnt angle along with SW Asian Siberian NE Euro Caucasian
    Quote Originally Posted by bmoney View Post

    Siberian must be a part of that grouping due to ANE


    Because the component is in lots of population groups besides the Baloch at significant numbers. So everything to the right of the y-axis has higher Baloch than everything to the left. You'll notice the Baloch, Makrani, and Brahui are in the 2nd Quadrant (not the Baloch quadrant), because this quadrant is high Baloch + high SW Asian/Caucasian etc. The further right you go the more Baloch. But not even the Baloch get pushed all the way down to the corner, because they aren't 100% of the component. In the 3rd quadrant are people with significant Baloch and but low SW Asian/Caucasian or they have significant SI coupled with Baloch. So what's actually defining placement to the right or left of the axis is Baloch v. SI and what defining above or below the axis are the other components.

    The PCA would turn out differently if he included more populations out of the region as they would force everyone to be bounded in the shape you're used to seeing.


    Last edited by khanabadoshi; 02-01-2018 at 10:06 PM.
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    Quote Originally Posted by poi View Post
    @jortita @reza -- updated the PCAs and added your scores.
    Thanks!

    Pretty much in the epicentre..

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    Quote Originally Posted by khanabadoshi View Post


    Because the component is in lots of population groups besides the Baloch at significant numbers. So everything to the right of the y-axis has higher Baloch than everything to the left. You'll notice the Baloch, Makrani, and Brahui are in the 2nd Quadrant (not the Baloch quadrant), because this quadrant is high Baloch + high SW Asian/Caucasian etc. The further right you go the more Baloch. But not even the Baloch get pushed all the way down to the corner, because they aren't 100% of the component. In the 3rd quadrant are people with significant Baloch and but low SW Asian/Caucasian or they have significant SI coupled with Baloch. So what's actually defining placement to the right or left of the axis is Baloch v. SI and what defining above or below the axis are the other components.

    The PCA would turn out differently if he included more populations out of the region as they would force everyone to be bounded in the shape you're used to seeing.


    Very well said! The quadrants, after revision 2, have shifted fyi. Could not figure out how to flip it back lol

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    Are the HGDP Pathan or HGDP Sindhi going to be included? Also, poi, what averages did you use for the Harappa Punjabi Khatri and Punjabi Jatt Sikh? The ones from Zack's spreadsheets or the ones from Dr_McNinja's spreadsheets? Or did you combine them?

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    Quote Originally Posted by Sapporo View Post
    Are the HGDP Pathan or HGDP Sindhi going to be included? Also, poi, what averages did you use for the Harappa Punjabi Khatri and Punjabi Jatt Sikh? The ones from Zack's spreadsheets or the ones from Dr_McNinja's spreadsheets? Or did you combine them?
    I have not merged mcninja or Khana's data yet, just used the calculator's plus anthrogenica members.

    Basically my process is documented in a script, so it can be replicated. All populations are categorized to have Region (e.g. SouthAsia), country, ethnicity, and caste if applicable. If there are multiple Punjabi Khatri data points, they are averaged as 1 Punjabi-Khatri.

    My plan is to use this script for any spreadsheet (after categorization) to generate clean dataset for PCA generation, including color coding etc.

    I will put this code on github if it is of interest to anyone.

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