Post Your GEDmatch Dodecad V3 Results

[Era]

^ My reply should have been to Gooding actually

With all due respect.. this thing seems to be way off.. Where did all this Eastern European come from?? Is it maybe deep ancestry? We have no documentation for Hungarian or Polish or any of this..
.

[Petalpusher]

^ My reply should have been to Gooding actually

I expected better from you benchmarkoid.

[Petalpusher]

I get the CEU thingie, how is that possible (love this smiley sorry)

We are all Americans as well after all. Can you pass in the US? Yes !

[Dr. Robotnik the Subbotnik]

With all due respect.. this thing seems to be way off.. Where did all this Eastern European come from?? Is it maybe deep ancestry? We have no documentation for Hungarian or Polish or any of this..
Gedmatch.Com

Dodecad V3 4-Ancestors Oracle
This program is based on 4-Ancestors Oracle Version 0.96 by Alexandr Burnashev.
Questions about results should be sent to him at: Alexandr.Burnashev@gmail.com
Original concept proposed by Sergey Kozlov.
Many thanks to Alexandr for helping us get this web version developed.

The GEDmatch version of Oracle may give slightly different results from Dienekes version. The GEDmatch version uses FST weighting in its calculations.

Admix Results (sorted):


# Population Percent
1 West_European 49.61
2 Mediterranean 27.02
3 East_European 14.58
4 West_Asian 6.75
5 South_Asian 1.21


Finished reading population data. 227 populations found.
12 components mode.

--------------------------------

Least-squares method.

Using 1 population approximation:
1 CEU @ 5.718964
2 German @ 6.413199
3 N._European @ 7.600528
4 Argyll @ 7.653700
5 Orcadian @ 7.776720
6 Orkney @ 8.171578
7 French @ 12.663768
8 French @ 13.027877
9 Slovenian @ 13.407598
10 Mixed_Germanic @ 14.985452
11 Dutch @ 15.985805
12 Hungarians @ 17.470774
13 Kent @ 18.275934
14 British_Isles @ 20.118895
15 British @ 20.347883
16 Cornwall @ 21.084616
17 Swedish @ 21.521936
18 Norwegian @ 23.126490
19 Irish @ 23.398907
20 French_Basque @ 24.091248

Using 2 populations approximation:
1 50% Hungarians +50% Kent @ 3.164591


Using 3 populations approximation:
1 50% French +25% Mixed_Germanic +25% Polish @ 1.382747


Using 4 populations approximation:
1 French + German + Hungarians + Orkney @ 1.167658
2 French + German + Hungarians + Orcadian @ 1.184730
3 French + German + Hungarians + Orcadian @ 1.315040
4 French + German + Hungarians + Orkney @ 1.321522
5 French + French + Mixed_Germanic + Polish @ 1.382747
6 French + German + Hungarians + Argyll @ 1.395325
7 Dutch + French + French + Mixed_Slav @ 1.397800
8 French + French + Mixed_Germanic + Polish @ 1.418770
9 Dutch + French + French + Polish @ 1.432998
10 Dutch + French + French + Mixed_Slav @ 1.435208
11 French + Hungarians + Argyll + Argyll @ 1.472697
12 CEU + French + German + Hungarians @ 1.503970
13 French + French + Kent + Mixed_Slav @ 1.509762
14 French + Hungarians + Orcadian + Argyll @ 1.509981
15 Cornwall + Mixed_Slav + Spaniards + Argyll @ 1.514307
16 Irish + Mixed_Slav + Spaniards + Argyll @ 1.523337
17 CEU + French + Hungarians + Argyll @ 1.525988
18 French + Hungarians + Orkney + Argyll @ 1.527730
19 Mixed_Germanic + Mixed_Germanic + Polish + Spaniards @ 1.536902
20 CEU + French + German + Hungarians @ 1.546423

Done.

Elapsed time 1.0636 seconds.

Mate you have an ancestors with the fucking name Wisnowska.

[Neon Knight]

Dodecad V3
West European 55.22%
Mediterranean 23.73%
East European 11.61%
West Asian 8.58%
South Asian 0.67%
Southeast Asian 0.13%
Neo African 0.06%

1 Argyll (1000 Genomes) 0.88
2 Orcadian (HGDP) 1.98
3 Orkney (1000 Genomes) 2.11
4 CEU (HapMap) 2.58
5 N._European (Xing) 2.65
6 German (Dodecad) 5.99
7 Mixed_Germanic (Dodecad) 7.29
8 Dutch (Dodecad) 8.63
9 Kent (1000 Genomes) 10.61
10 French (HGDP) 12.11
11 British_Isles (Dodecad) 12.17
12 British (Dodecad) 12.49
13 French (Dodecad) 12.57
14 Cornwall (1000 Genomes) 13.13
15 Swedish (Dodecad) 14.05

I think those are my best results for any of the GEDmatch calculators.


My mum's results:

1 West_European 53.78
2 Mediterranean 23.4
3 East_European 11.61
4 West_Asian 10.35
5 Northwest_African 0.83
6 Neo_African 0.04

1 Argyll (1000 Genomes) 2.84
2 N._European (Xing) 3.36
3 CEU (HapMap) 3.55
4 Orcadian (HGDP) 3.96
5 Orkney (1000 Genomes) 4.16
6 German (Dodecad) 6.26
7 Mixed_Germanic (Dodecad) 8.02
8 Dutch (Dodecad) 9.82
9 Kent (1000 Genomes) 11.82
10 French (HGDP) 12.36
11 French (Dodecad) 12.99
12 British_Isles (Dodecad) 13.45
13 British (Dodecad) 13.75
14 Cornwall (1000 Genomes) 14.29
15 Swedish (Dodecad) 15.23

[Graham]

It's hard to compare like-for-like. The overfit & calc effect. have said before. 1000 genomes and Dodecad are out of sink on Oracle I think.

[Siginulfo]

Admix Results (sorted):

# Population Percent
1 Mediterranean 35.70
2 West_European 23.02
3 West_Asian 20.68
4 Southwest_Asian 10.41
5 East_European 6.93
6 Northwest_African 2.77


Finished reading population data. 227 populations found.
12 components mode.

--------------------------------

Least-squares method.

Using 1 population approximation:
1 Ashkenazy_Jews @ 6.041652
2 Ashkenazi @ 7.060810
3 Tuscan @ 8.107965
4 Tuscan @ 8.902706
5 TSI @ 9.439683
6 O_Italian @ 9.489076
7 C_Italian @ 10.679910
8 S_Italian_Sicilian @ 13.275015
9 Morocco_Jews @ 13.440388
10 Tuscan @ 14.786115
11 Sicilian @ 15.438376
12 Greek @ 15.460330
13 S_Italian @ 17.109985
14 N_Italian @ 17.867369
15 Sephardic_Jews @ 18.123594
16 Romanians_14 @ 19.084055
17 North_Italian @ 21.631311
18 Balkans @ 24.535576
19 Turkish @ 27.395041
20 Portuguese @ 27.628532

Using 2 populations approximation:
1 50% Ashkenazy_Jews +50% Tuscan @ 3.187739


Using 3 populations approximation:
1 50% O_Italian +25% Samaritians +25% Slovenian @ 1.723940


Using 4 populations approximation:
1 German + O_Italian + Samaritians + Sicilian @ 1.460840
2 Ashkenazy_Jews + Druze + Sardinian + Slovenian @ 1.467802
3 Cypriots + German + Morocco_Jews + O_Italian @ 1.481698
4 Ashkenazi + Druze + Sardinian + Slovenian @ 1.489110
5 Cypriots + German + Sephardic_Jews + Tuscan @ 1.680799
6 Druze + French_Basque + Morocco_Jews + Romanians_14 @ 1.682252
7 Morocco_Jews + North_Italian + Samaritians + Slovenian @ 1.721181
8 O_Italian + O_Italian + Samaritians + Slovenian @ 1.723940
9 Cypriots + German + Sephardic_Jews + Tuscan @ 1.725565
10 Ashkenazi + North_Italian + Samaritians + Slovenian @ 1.755064
11 Druze + Morocco_Jews + North_Italian + Slovenian @ 1.764470
12 French_Basque + Georgia_Jews + Morocco_Jews + Romanians_14 @ 1.770607
13 Balkans + Druze + French_Basque + Morocco_Jews @ 1.780563
14 Greek + Morocco_Jews + Sephardic_Jews + N._European @ 1.837899
15 Ashkenazy_Jews + German + Sephardic_Jews + Sephardic_Jews @ 1.851299
16 Ashkenazi + Iraq_Jews + Sardinian + Slovenian @ 1.859277
17 French_Basque + Iraq_Jews + Morocco_Jews + Romanians_14 @ 1.862784
18 Ashkenazy_Jews + German + S_Italian + Sephardic_Jews @ 1.895536
19 Ashkenazi + German + S_Italian_Sicilian + Sephardic_Jews @ 1.904512
20 Azerbaijan_Jews + Morocco_Jews + Sardinian + Slovenian @ 1.920581

[DRUM]

..

Hey just a question if you don't mind.. Wich company did you use to get a such accurate Y-DNA result?

[Sikeliot]

Here is mine.

4 way Druze-Polish-Spanish-Spanish makes sense. Druze + Spanish comes out Sicilian. Then Spanish is capturing the Portuguese part, and Polish ancestry is my remaining quarter. The African gets sucked up, and amounts to 1.25% East, 0.37% Neo-African and 0.12% PaleoAfrican = 1.74%.


# Population Percent
1 Mediterranean 36.33
2 West_European 29.82
3 East_European 12.67
4 West_Asian 12.08
5 Southwest_Asian 5.86
6 Northwest_African 1.51
7 East_African 1.25


Finished reading population data. 227 populations found.
12 components mode.

--------------------------------

Least-squares method.

Using 1 population approximation:
1 Tuscan @ 10.439878
2 Tuscan @ 10.483774
3 TSI @ 11.486133
4 N_Italian @ 12.118563
5 O_Italian @ 13.650196
6 Romanians_14 @ 14.481263
7 Tuscan @ 16.129522
8 North_Italian @ 16.988232
9 Balkans @ 17.451427
10 C_Italian @ 18.148546
11 Ashkenazy_Jews @ 18.784306
12 Slovenian @ 19.529737
13 Portuguese @ 19.880548
14 Hungarians @ 19.995298
15 Ashkenazi @ 20.129622
16 IBS @ 21.466003
17 Spanish @ 22.271790
18 Greek @ 22.583429
19 Spaniards @ 22.668583
20 S_Italian_Sicilian @ 23.486015

Using 2 populations approximation:
1 50% C_Italian +50% Slovenian @ 4.636837


Using 3 populations approximation:
1 50% Hungarians +25% Morocco_Jews +25% Sardinian @ 1.962076


Using 4 populations approximation:
1 Druze + Polish + Spanish + Spanish @ 1.160456
2 C_Italian + French_Basque + Morocco_Jews + Polish @ 1.213673
3 Druze + Polish + Spaniards + Spanish @ 1.234654
4 Druze + IBS + Polish + Spanish @ 1.287314
5 Druze + IBS + Polish + Spaniards @ 1.335111
6 Polish + Sephardic_Jews + Spaniards + TSI @ 1.343173
7 French_Basque + Mixed_Slav + O_Italian + Sephardic_Jews @ 1.350411
8 Ashkenazi + French_Basque + Polish + Sicilian @ 1.411326
9 Druze + IBS + IBS + Polish @ 1.459146
10 Morocco_Jews + Polish + Spaniards + Tuscan @ 1.460306
11 IBS + Polish + S_Italian_Sicilian + Tuscan @ 1.462150
12 Mixed_Slav + S_Italian_Sicilian + Spanish + Tuscan @ 1.480100
13 Ashkenazi + O_Italian + Polish + Spanish @ 1.498627
14 Polish + Sephardic_Jews + Spaniards + Tuscan @ 1.517170
15 Polish + S_Italian_Sicilian + Spanish + Tuscan @ 1.542098
16 Mixed_Slav + S_Italian_Sicilian + Spaniards + Tuscan @ 1.554551
17 IBS + Mixed_Slav + S_Italian_Sicilian + Tuscan @ 1.562692
18 IBS + Polish + S_Italian_Sicilian + Tuscan @ 1.574229
19 Druze + Polish + Spaniards + Spaniards @ 1.574871
20 Sardinian + Sephardic_Jews + Slovenian + Slovenian @ 1.581996

[noricum]

1 West_European 41.86
2 Mediterranean 24.14
3 East_European 21.82
4 West_Asian 8.66
5 Southwest_Asian 2.01
6 South_Asian 1.17
7 Palaeo_African 0.1
8 Northeast_Asian 0.08
9 East_African 0.08
10 Northwest_African 0.04
11 Southeast_Asian 0.03

Single Population Sharing:


# Population (source) Distance
1 Slovenian (Xing) 2.34
2 Hungarians (Behar) 6.24
3 German (Dodecad) 11.02
4 CEU (HapMap) 14.65
5 N._European (Xing) 15
6 Argyll (1000 Genomes) 15.5
7 Orcadian (HGDP) 16.25
8 Orkney (1000 Genomes) 16.51
9 Balkans (Dodecad) 17.87
10 French (Dodecad) 20.3
11 Romanians_14 (Behar) 20.51
12 French (HGDP) 20.72
13 Mixed_Germanic (Dodecad) 22.07
14 FIN (1000Genomes) 22.62
15 Polish (Dodecad) 23
16 Mixed_Slav (Dodecad) 23.46
17 Dutch (Dodecad) 23.57
18 Tuscan (Xing) 24.4
19 Tuscan (Henn) 24.46
20 TSI (HapMap) 24.86

Mixed Mode Population Sharing:


# Primary Population (source) Secondary Population (source) Distance
1 70.9% Hungarians (Behar) + 29.1% N._European (Xing) @ 1.12
2 78.3% Hungarians (Behar) + 21.7% Mixed_Germanic (Dodecad) @ 1.24
3 84.8% Slovenian (Xing) + 15.2% German (Dodecad) @ 1.27
4 58.7% Balkans (Dodecad) + 41.3% Swedish (Dodecad) @ 1.3
5 89.6% Slovenian (Xing) + 10.4% Orkney (1000 Genomes) @ 1.36
6 83.1% Hungarians (Behar) + 16.9% Irish (Dodecad) @ 1.36
7 89.5% Slovenian (Xing) + 10.5% Orcadian (HGDP) @ 1.37
8 79.4% Hungarians (Behar) + 20.6% Dutch (Dodecad) @ 1.39
9 88.6% Slovenian (Xing) + 11.4% CEU (HapMap) @ 1.4
10 82.2% Hungarians (Behar) + 17.8% Cornwall (1000 Genomes) @ 1.42
11 89.4% Slovenian (Xing) + 10.6% Argyll (1000 Genomes) @ 1.44
12 81.9% Hungarians (Behar) + 18.1% British (Dodecad) @ 1.45
13 81.7% Hungarians (Behar) + 18.3% British_Isles (Dodecad) @ 1.46
14 93.8% Slovenian (Xing) + 6.2% British_Isles (Dodecad) @ 1.49
15 80.9% Hungarians (Behar) + 19.1% Kent (1000 Genomes) @ 1.5
16 93.9% Slovenian (Xing) + 6.1% British (Dodecad) @ 1.5
17 89.3% Slovenian (Xing) + 10.7% N._European (Xing) @ 1.51
18 93.5% Slovenian (Xing) + 6.5% Kent (1000 Genomes) @ 1.51
19 93% Slovenian (Xing) + 7% Dutch (Dodecad) @ 1.52
20 94.4% Slovenian (Xing) + 5.6% Irish (Dodecad) @ 1.52

1 West_European 41.86
2 Mediterranean 24.14
3 East_European 21.82
4 West_Asian 8.66
5 Southwest_Asian 2.01
6 South_Asian 1.17


--------------------------------

Least-squares method.

Using 1 population approximation:
1 Slovenian @ 2.571139
2 Hungarians @ 6.907999
3 German @ 12.276849
4 CEU @ 16.252377
5 N._European @ 16.638920
6 Argyll @ 17.222378
7 Orcadian @ 18.060289
8 Orkney @ 18.349369
9 Balkans @ 19.911499
10 French @ 22.405420
11 French @ 22.862059
12 Romanians_14 @ 22.904881
13 Mixed_Germanic @ 24.492224
14 FIN @ 24.807947
15 Polish @ 25.385614
16 Mixed_Slav @ 25.861372
17 Dutch @ 26.163574
18 Tuscan @ 27.074053
19 Tuscan @ 27.113169
20 TSI @ 27.572634

Using 2 populations approximation:
1 50% Slovenian +50% Slovenian @ 2.571139


Using 3 populations approximation:
1 50% Hungarians +25% N._European +25% Slovenian @ 0.873275


Using 4 populations approximation:
1 CEU + Lithuanian + O_Italian + Argyll @ 0.830504
2 Lithuanian + O_Italian + Orcadian + N._European @ 0.853406
3 Hungarians + Hungarians + N._European + Slovenian @ 0.873275
4 Lithuanian + O_Italian + Orkney + N._European @ 0.911431
5 Lithuanian + Tuscan + N._European + N._European @ 0.919571
6 Belorussian + German + TSI + Argyll @ 0.926123
7 Polish + Romanians_14 + N._European + N._European @ 0.927633
8 CEU + Lithuanian + O_Italian + N._European @ 0.949955
9 Lithuanian + O_Italian + Argyll + N._European @ 0.950992
10 Belorussian + German + Orkney + Tuscan @ 0.954775
11 Irish + Lithuanians + Tuscan + Slovenian @ 0.969466
12 CEU + Lithuanian + O_Italian + Orkney @ 0.971520
13 Irish + Lithuanian + Tuscan + Slovenian @ 0.992398
14 Belorussian + German + Argyll + Tuscan @ 1.008806
15 CEU + Lithuanian + O_Italian + Orcadian @ 1.011846
16 Lithuanian + O_Italian + Argyll + Argyll @ 1.016265
17 Belorussian + German + Orkney + TSI @ 1.019295
18 Lithuanians + O_Italian + Argyll + N._European @ 1.032802
19 Lithuanian + Tuscan + Argyll + N._European @ 1.040707
20 Belorussian + German + Orcadian + Tuscan @ 1.045036