My Autossomal Africa9 Admixture Proportions
 |
| GENY DOS SANTOS FLORENTINO |
My Autossomal Africa9 Admixture Proportions
The Africa9 admixture calculator is courtesy of Dienekes Pontikos and was developed as part of the Dodecad Ancestry Project; more information here.
Kit Number: F229750 Iteration: 1000 Delta-Q: 1.802786e-05 Elapsed Time: 42.39 seconds
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Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions 'calculator' model remains the property of its developer.
This program is based on
'Oracle v1' by Dienekes Pontikos. His original program was
developed as part of the Dodecad Ancestry
Project. More
information on Dienekes' orignal program can be found here.
Many thanks also to Zack Ajmal for helping us get this web version of Dienekes' Oracle program developed.
Many thanks also to Zack Ajmal for helping us get this web version of Dienekes' Oracle program developed.
Africa9 Oracle
results:
Kit F229750
Admix Results (sorted):
Admix Results (sorted):
#
|
Population
|
Percent
|
1
|
W_Africa
|
53.92
|
2
|
S_Africa
|
14.22
|
3
|
Biaka
|
9.54
|
4
|
E_Africa
|
8.57
|
5
|
Europe
|
6.65
|
6
|
NW_Africa
|
3.36
|
7
|
Mbuti
|
2.09
|
8
|
San
|
1.65
|
Single Population Sharing:
#
|
Population
(source)
|
Distance
|
1
|
Fang
|
12.08
|
2
|
Kongo
|
13.37
|
3
|
Bamoun
|
15.24
|
4
|
Luhya
|
17.28
|
5
|
Kaba
|
19.51
|
6
|
Bantu_N.E.
|
20.13
|
7
|
Hausa
|
21.85
|
8
|
Igbo
|
23.16
|
9
|
Mada
|
24.1
|
10
|
Yoruba
|
24.5
|
11
|
Brong
|
27.53
|
12
|
Mandenka
|
33.5
|
13
|
Fulani
|
33.81
|
14
|
Bulala
|
37
|
15
|
Maasai
|
56.94
|
16
|
Morocco_S
|
59.53
|
17
|
HADZA
|
64.19
|
18
|
Xhosa
|
64.56
|
19
|
SANDAWE
|
65.02
|
20
|
Algeria
|
66.19
|
Mixed Mode Population Sharing:
#
|
Primary
Population (source)
|
Secondary
Population (source)
|
Distance
|
|||||
1
|
89.2%
|
Kongo
|
+
|
10.8%
|
North_Italian
|
@
|
7.4
|
|
2
|
92.3%
|
Fang
|
+
|
7.7%
|
French_Basque
|
@
|
7.57
|
|
3
|
90.7%
|
Fang
|
+
|
9.3%
|
North_Italian
|
@
|
7.59
|
|
4
|
89.2%
|
Kongo
|
+
|
10.8%
|
Tuscan
|
@
|
7.65
|
|
5
|
86.1%
|
Kongo
|
+
|
13.9%
|
North_African
(Dodecad)
|
@
|
7.7
|
|
6
|
91.1%
|
Kongo
|
+
|
8.9%
|
French_Basque
|
@
|
7.71
|
|
7
|
90.7%
|
Fang
|
+
|
9.3%
|
Tuscan
|
@
|
7.81
|
|
8
|
88.1%
|
Kongo
|
+
|
11.9%
|
Morocco_Jews
|
@
|
7.84
|
|
9
|
89.9%
|
Fang
|
+
|
10.1%
|
Morocco_Jews
|
@
|
8.13
|
|
10
|
83.2%
|
Bamoun
|
+
|
16.8%
|
HADZA
|
@
|
8.2
|
|
11
|
88.5%
|
Fang
|
+
|
11.5%
|
North_African
(Dodecad)
|
@
|
8.24
|
|
12
|
87.5%
|
Kongo
|
+
|
12.5%
|
Morocco_N
|
@
|
8.36
|
|
13
|
88.6%
|
Kongo
|
+
|
11.4%
|
North_African_Jews
(Dodecad)
|
@
|
8.4
|
|
14
|
86%
|
Kongo
|
+
|
14%
|
HADZA
|
@
|
8.42
|
|
15
|
86.3%
|
Kongo
|
+
|
13.7%
|
Algeria
|
@
|
8.42
|
|
16
|
83.6%
|
Bamoun
|
+
|
16.4%
|
SANDAWE
|
@
|
8.56
|
|
17
|
90.5%
|
Fang
|
+
|
9.5%
|
North_African_Jews
(Dodecad)
|
@
|
8.6
|
|
18
|
89.6%
|
Fang
|
+
|
10.4%
|
Morocco_N
|
@
|
8.65
|
|
19
|
68.4%
|
Fang
|
+
|
31.6%
|
Bantu_N.E.
|
@
|
8.68
|
|
20
|
86.4%
|
Kongo
|
+
|
13.6%
|
SANDAWE
|
@
|
8.69
|
|
Gedmatch.Com
Africa9 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.
Revised: Dec 6, 2012
9 components mode.
Component threshold auto-set to 1.340%. Admix results below that value will not be considered.
Kit Number: F229750
Admix Results (sorted):
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.
Revised: Dec 6, 2012
9 components mode.
Component threshold auto-set to 1.340%. Admix results below that value will not be considered.
Kit Number: F229750
Admix Results (sorted):
#
|
Population
|
Percent
|
1
|
W_Africa
|
53.92
|
2
|
S_Africa
|
14.22
|
3
|
Biaka
|
9.54
|
4
|
E_Africa
|
8.57
|
5
|
Europe
|
6.65
|
6
|
NW_Africa
|
3.36
|
7
|
Mbuti
|
2.09
|
8
|
San
|
1.65
|
--------------------------------
Least-squares method.
Using 1 population approximation:
1 Fang @ 12.507
2 Kongo @ 14.117
3 Bamoun @ 16.561
4 Luhya @ 18.944
5 Kaba @ 21.147
6 Bantu_N.E. @ 22.137
7 Hausa @ 24.144
8 Igbo @ 25.655
9 Mada @ 26.187
10 Yoruba @ 27.184
54 iterations.
Using 2 populations approximation:
1 50% Fang +50% Luhya @ 9.545
2 50% Kongo +50% Luhya @ 10.098
3 50% Bamoun +50% Luhya @ 10.166
4 50% Bantu_N.E. +50% Fang @ 10.242
5 50% Bamoun +50% Bantu_N.E. @ 11.008
6 50% Bantu_N.E. +50% Kongo @ 11.134
7 50% Fang +50% Fang @ 12.507
8 50% Fang +50% Kongo @ 12.638
9 50% Igbo +50% Luhya @ 13.294
10 50% Hausa +50% Luhya @ 13.437
1485 iterations.
Using 3 populations approximation:
1 50% Fang +25% Bantu_N.E. +25% Fang @ 8.723
2 50% Fang +25% Bantu_N.E. +25% Kongo @ 8.783
3 50% Fang +25% Kongo +25% Luhya @ 9.007
4 50% Fang +25% Bantu_N.E. +25% Fulani @ 9.043
5 50% Fang +25% Fang +25% Luhya @ 9.063
6 50% Fang +25% Bamoun +25% Bantu_N.E. @ 9.094
7 50% Fang +25% Fulani +25% Luhya @ 9.131
8 50% Fang +25% Bantu_S.E._Pedi +25% Mada @ 9.289
9 50% Kongo +25% Bantu_N.E. +25% Fang @ 9.341
10 50% Fang +25% Bamoun +25% Luhya @ 9.367
18960 iterations.
Using 4 populations approximation:
1 Bantu_N.E. + Fang + Fang + Fang @ 8.723
2 Bantu_N.E. + Fang + Fang + Kongo @ 8.783
3 Fang + Fang + Kongo + Luhya @ 9.007
4 Bantu_N.E. + Fang + Fang + Fulani @ 9.043
5 Fang + Fang + Fang + Luhya @ 9.063
6 Bamoun + Bantu_N.E. + Fang + Fang @ 9.094
7 Fang + Fang + Fulani + Luhya @ 9.131
8 Bantu_S.E._Pedi + Fang + Fang + Mada @ 9.289
9 Bamoun + Bantu_S.E._Pedi + Fang + Luhya @ 9.305
10 Bantu_S.E._Pedi + Fang + Kaba + Luhya @ 9.326
11 Bantu_N.E. + Fang + Kongo + Kongo @ 9.341
12 Bamoun + Fang + Fang + Luhya @ 9.367
13 Bamoun + Bantu_N.E. + Bantu_S.E._Pedi + Fang @ 9.372
14 Fang + Fulani + Kongo + Luhya @ 9.391
15 Bantu_S.E._S.Sotho + Fang + Fang + Mada @ 9.409
16 Bantu_N.E. + Fang + Fulani + Kongo @ 9.416
17 Bantu_S.E._Pedi + Fang + Fang + Luhya @ 9.445
18 Fang + Kongo + Kongo + Luhya @ 9.445
19 Bantu_N.E. + Bantu_S.E._Pedi + Fang + Fang @ 9.457
20 Bantu_S.E._S.Sotho + Fang + Fulani + Mada @ 9.521
30746 iterations.
Done.
Elapsed time 0.0293 seconds.
Gedmatch.Com
Africa9
Oracle-x Population Fitting
This program is based on
Larry Smiser's Population Fitting spreadsheet.
Questions about the method or results should be sent to him at lwsmiser@gmail.com
Finished reading population data. 54 populations found.
9 population clusters.
Kit Number: F229750
Admix Results:
Questions about the method or results should be sent to him at lwsmiser@gmail.com
Finished reading population data. 54 populations found.
9 population clusters.
Kit Number: F229750
Admix Results:
#
|
Population
|
Percent
|
1
|
Europe
|
6.65
|
2
|
NW_Africa
|
3.36
|
3
|
SW_Asia
|
0.00
|
4
|
E_Africa
|
8.57
|
5
|
S_Africa
|
14.22
|
6
|
Mbuti
|
2.09
|
7
|
W_Africa
|
53.92
|
8
|
Biaka
|
9.54
|
9
|
San
|
1.65
|
Pct. Calc. Option 2
0
|
Unable
to determine
|
0.01%
|
1
|
Bamoun
|
57.86%
|
2
|
Fang
|
15.37%
|
3
|
SANDAWE
|
7.22%
|
4
|
French_Basque
|
7.17%
|
5
|
Fulani
|
4.23%
|
6
|
Xhosa
|
3.51%
|
7
|
Bantu_S.E._Pedi
|
2.72%
|
8
|
TUNISIA
|
0.96%
|
9
|
HADZA
|
0.95%
|
10
|
Bantu_S.W._Ovambo
|
0.00%
|
Total RMSD: 0.776414
Elapsed time 0.5373 seconds.
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