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Thread: Dodecad Ancestry Project

  1. #331
    Never meant to be here Frederick's Avatar
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    My own "Per Chromosome":

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    Sahsons per Chromosome:

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    Please do me Fredrick, DOD197.

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    Veteran Member Loki's Avatar
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    Mine too pls! DOD442
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    Quote Originally Posted by Commerce & Industry View Post
    Edit some easier instructions:
    Open up dv3.par in wordpad and change "genomewide" to "bychr" no quotes then in R enter these commands:

    setwd('C:\file path to\DIYDodecad') or just File>Change Dir and locate the DIYDodecad folder

    source('standardize.r')

    standardize('mygenome.txt', company='23andMe')

    system('DIYDodecadWin dv3.par')
    Could you please tell me how i generate my graph besides those instructions?
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    Quote Originally Posted by AlexDelarge View Post
    Could you please tell me how i generate my graph besides those instructions?

    1. Open up the text file in either excel or open office. It will go through a wizard just keep hitting next till that goes away.

    2. The top row will be messed up a bit so just re-type that in so the column headers are correct

    3. Then select ONLY the columns for the different populations percentages(don't include chr or #SNPs)

    4. Now in Excel 2007


    For 2003 or OpenOffice just go to Insert>Chart after selecting the data and for Open Office follow the wizard>
    Screenshot of OpenOffice don't have a copy of excel 2003

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    I need your raw data files to do it.
    Or you try it on your own.

    If you already have "R" and all this stuff (that was also used for Oracle)

    Then it works like this (slaps Dienekes face for this complicated way):

    1. Download DYS 2.0 and unpack it.
    2. Put your file into the directory of the DYS 2.0 thingy.
    3. rename it to "Johndoe"
    4. start "R" and look under "File" section of the menue for something to change the working directory. Change it to the directory of your DYS 2.0 thingy.
    5. type source('standardize.r') into your "R"
    6. type standardize('johndoe.txt', company='23andMe') if its 23andMe Data (here you could also put the name of your file instead of Johndoe but... renaming the file into Johndoe is a little faster)
    OR
    standardize('johndoe.csv', company='ftdna') if it is FTDNA Data

    7. Open the DV3.PAR (the PAR not the TXT!) with wordpad (not with notepad!)

    you find this:

    1D-7
    12
    genotype.txt
    166462
    dv3.txt
    dv3.12.F
    dv3.alleles
    verbose
    genomewide

    exchange "genomewide" with "bychr" and save.

    8. type system('DIYDodecadWin dv3.par') to the "R" window
    Now it takes some time, depending on the speed of your computer. Some claim it takes 10 or 15 Minutes. With my laptop (ASUS G73J Gaminglaptop) it takes 5 Minutes. *shrugs*

    9. Now there is a "bychr" textfile in your DYS 2.0 folder.

    10. Now if you dont have an American version of Excel, it may be that "." shiuld be exchanged to ",". (for Germans. Dont know if other nations also use "," in numbers and not "." (i learned it the hard way, after my fucking Excell made all the numbers to DATES all the fucking time. GRRRRR (And I am an Excel noob)

    You do this like this:
    Open in notepad or whatever. Click CTRL+H, and let it replace all "." with ",".

    So, now you can save it and open it with Excel. Tell it you want to make a change to the collumns, then tell it that a SPACE is the mark for a new collumn.

    Finnish, there you have the stuff in excel, with all the collumns correct. (and not turning 7.12 into 7th December ha ha)

    And then you chose the stuff (except the first collumn) and insert a graph.

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    This is very hard to do in Open Office in portuguese, i had to download the trial version of Excel 2007 to do this. But it turned out well



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  9. #339
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    Interesting, when I do it "bychr", my West European average is higher, and South European lower.
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    Here are my normal results by the way:

    Mediterranean: 42.86%
    West European: 38.33%
    Northwest African: 7.25%
    West Asian: 5.73%
    East European: 2.94%
    Neo African: 1.07%
    East African: 0.94%
    South Asian 0.76%
    Paleo African 0.11%

    Southwest Asian: 0%
    Northeast Asian: 0%
    Southeast Asian: 0%
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