^ My reply should have been to Gooding actually
Quote:
Originally Posted by Gooding
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^ My reply should have been to Gooding actually
Quote:
Originally Posted by Gooding
I expected better from you benchmarkoid.Quote:
Originally Posted by Chloe
We are all Americans as well after all. Can you pass in the US? Yes !Quote:
Originally Posted by Eleonore
Mate you have an ancestors with the fucking name Wisnowska.Quote:
Originally Posted by Gooding
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
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.
http://s29.postimg.org/5i2vgs29j/image.jpghttp://s23.postimg.org/gp0hzsfwr/image.jpghttp://s29.postimg.org/ftf89ftyv/v31.jpg
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
Hey just a question if you don't mind.. Wich company did you use to get a such accurate Y-DNA result?Quote:
Originally Posted by Siginulfo
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
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