Dodecad Ancestry Project

I know Dienekes didnt recommented using Oracle on tiny DNA fragments instead of genomewide but I wanted to know what would be the result anyways. :p

I flushed every single Chromosom through the Oracle thing and these are the top nation for each Chromosom:
(only Nations and no doublettes)

Chromosom 1: Orkney Island
Chromosom 2: Slovenia
Chromosom 3: Germany
Chromosom 4: Sweden
Chromosom 5: Germany
Chromosom 6: Slovenia
Chromosom 7: Germany
Chromosom 8: Finland
Chromosom 9: Germany
Chromosom 10: Netherland
Chromosom 11: Finland
Chromosom 12: France
Chromosom 13: Germany
Chromosom 14:Finland
Chromosom 15: Slovenia
Chromosom 16: Finland
Chromsom 17: France
Chromosom 18: Germany
Chromosom 19: Germany
Chromosom 20: Germany
Chromosom 21: Norway
Chromosom 22: Italy

8/22 Germany
4/22 Finland (because of my Lithuanian Great Great Grandmom maybe)
3/22 Slovenia
2/22 France
1/22 Orkney Island
1/22 Norway
1/22 Sweden
1/22 Netherland
1/22 Italy

EDIT:
Needed to Edit, my Great Grandmom into my Great Great GRandmom... lol

Quote:

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Originally Posted by Loki

Interesting, when I do it "bychr", my West European average is higher, and South European lower.

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I'd imagine that it is due to the different amounts of SNPs in your chromosomes. Chromosome 1 has 13376 SNPs, while chromosome 22 has but 2688. Consequently, Chromosome 1 influences the actual average to a much greater degree. Simply averaging by chromosome results will not take this into account, and hence will yield little.

Why does everyone get wog and chink scores on this, but on Eurogenes and previous Dienekes tests they get no non-Euro?

Quote:

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Originally Posted by Imperivm

Why does everyone get wog and chink scores on this, but on Eurogenes and previous Dienekes tests they get no non-Euro?

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Dienekes said, the tool produces more "noise" than the calculations he officially does. I think he refers to these small percentages of African and Asian.

My "bychr."

Code:

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Chr        E_Euro        W_Euro        Medite        Neo_Af        W_Asia        S_Asia        N_E_As        S_E_As        E_Afri        S_W_As        N_W_Af        Pal_Af
1        2.57        0.37        23.6        0        52.23        0        1.97        0        0.01        19.25        0        0
2        2.43        7.58        22.79        0        43.63        0.02        0        0        0        23.54        0.02        0
3        1.34        2.82        31.18        0.02        45.32        9.02        0        0        0.36        8.92        1.02        0
4        0.01        2.73        17.59        0.09        50.22        11.48        1.04        0        0        16.84        0        0
5        0        4.67        31.83        0        30.77        5.28        0.26        0        1.03        26.16        0        0
6        6.09        0.04        23.46        0        44.85        0.56        2.06        0        0        21        1.94        0
7        0.07        0        28.7        0.32        45.66        3.18        0.28        0.74        2.85        18.21        0        0
8        0.03        0        27.38        0.3        49.83        2.77        0        0.73        0        15        3.96        0
9        4.26        6.9        23.51        0        38.02        10.47        0        0        0.75        16.09        0        0
10        8.41        1.35        16.76        0        41.03        9.85        0        1.95        0        17.47        2.28        0.89
11        0        0        21.4        0        50.13        0.01        0        0        0        21.33        7.12        0
12        4.96        6.81        20.94        0        44.62        0.37        0        0.17        0        22.13        0        0
13        0        0.04        23.8        0        46.45        10.43        0        5.86        0        12.84        0        0.58
14        1.47        2.49        14.57        0.01        44.33        12.26        1.66        0        0.01        20.57        1.45        1.16
15        0.01        11.11        23.39        0        51.67        0        0        0        1.05        10.51        2.25        0
16        0.02        4.23        31.48        0        41.27        5.44        0.17        0        0        17.38        0        0
17        0        18.13        25.62        0        36.75        2.32        0        0        0        17.15        0.02        0
18        0.03        0        20.58        0        39.15        0        0        3.58        3.03        33.63        0        0
19        0        0        24.13        0        42.68        4.25        0        2.13        5.94        19.18        1.69        0
20        5.33        0        29.48        0        41.21        5.54        0        3.95        0.3        14.18        0.01        0
21        7.88        0.01        19.45        1.58        44.59        4.45        4.19        2.48        0        15.36        0        0
22        0        14.23        24.56        0        34.45        2.79        0        0.13        0        23.84        0        0

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I just received admixture analysis results from Dienekes. I am DOD804 on the spreadsheet. I sorted them. :)

Mediterranean 34.8
West_Asian 27.4
West_European 17.2
Southwest_Asian 11.4
Northwest_African 6.6
East_European 1.5
East_African 1.1
Neo_African 0.2
South_Asian 0
Northeast_Asian 0
Southeast_Asian 0
Palaeo_African 0

My DIY Dodecad2.0 results


Genome-wide results:


41.89% Mediterranean
41.69% West_European
5.50% Northwest_African
3.34% Southwest_Asian
3.27% West_Asian
1.81% East_African
1.24% East_European
0.63% Southeast_Asian
0.61% Neo_African
0.01% South_Asian
0.00% Northeast_Asian
0.00% Palaeo_African


By chromossome:


http://i116.photobucket.com/albums/o...Imagem16-1.png
http://i116.photobucket.com/albums/o...Imagem17-2.png

Quote:

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Originally Posted by Frederick

4/22 Finland (because of my Lithuanian Great Great Grandmom maybe)

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'FIN' and 'German_D' are Dodecad's primary way of explaining West Europeans with a significant East European element. Germans_D and FIN (not Finnish_D) are principally rather similar to each other, except that Finns are less Mediterranean.

25% EE, 55% WE and 20% Med = German_D, then FIN
25% EE, 55% WE, 10% Med, 10% scattered = FIN, then German_D

A hypothetical Prussian German would turn out FIN, for instance: he will be mostly WE, with a moderate EE and little Med. Lithuanians do have the single highest EE percentage of all nations there, but it's unlikely that such a far-away ancestor would be a significant influence.

Quote:

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Originally Posted by Humanophage

'FIN' and 'German_D' are Dodecad's primary way of explaining West Europeans with a significant East European element. Germans_D and FIN (not Finnish_D) are principally rather similar to each other, except that Finns are less Mediterranean.

25% EE, 55% WE and 20% Med = German_D, then FIN
25% EE, 55% WE, 10% Med, 10% scattered = FIN, then German_D

A hypothetical Prussian German would turn out FIN, for instance: he will be mostly WE, with a moderate EE and little Med. Lithuanians do have the single highest EE percentage of all nations there, but it's unlikely that such a far-away ancestor would be a significant influence.

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Hm. I see.
Its 3 times "FIN" and 1 time "Finnish".

My" bychr"

http://i53.tinypic.com/121flv6.png

Everything else is to small to tell if it's noise or not.