1-ANTONIO FLORENTINO DOCUMENTOS GENETICOS

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MY NATIVE AMERICAN FAMILY (MINHA FAMILIA NATIVO AMERICANO)


MY NATIVE AMERICAN FAMILY (MINHA FAMILIA NATIVO AMERICANO)

7_Fotos_Gabriel_My son

MY SON GABRIEL FLORENTINO

6_My_FTDNA_MT_DNA_Certificate

MY SON GABRIEL FLORENTINO

 

MY SON GABRIEL FLORENTINO

MY SON GABRIEL FLORENTINO

MY SON GABRIEL

MY SON GABRIEL FLORENTINO

Page_2_all-native-american-maps_Gabriel

MY SON GABRIEL FLORENTINO

MY SON GABRIEL

MY SON GABRIEL FLORENTINO

Page_3_all-native-american-maps_Gabriel

MY SON GABRIEL FLORENTINO

MY SON GABRIEL

MY SON GABRIEL FLORENTINO

Page_4_all-native-american-maps_Gabriel

MY SON GABRIEL FLORENTINO

Meu_Pai_João_Florentino

MY FATHER JOÃO FLORENTINO

4_FTDNA_mtDNA_A2_João_Florentino

MY FATHER JOÃO FLORENTINO

MY FATHER JOÃO FLORENTINO

MY FATHER JOÃO FLORENTINO

9_all-native-american-maps (1)

MY FATHER JOÃO FLORENTINOMY FATHER JOÃO FLORENTINO

MY FATHER JOÃO FLORENTINO

9_all-native-american-maps (2)

MY FATHER JOÃO FLORENTINO

MY FATHER JOÃO FLORENTINO

MY FATHER JOÃO FLORENTINO

MY FATHER JOÃO FLORENTINO

MY FATHER JOÃO FLORENTINO

MY FATHER JOÃO FLORENTINO

MY FATHER JOÃO FLORENTINO

MY FATHER JOÃO FLORENTINO

MY FATHER JOÃO FLORENTINO

MY WIFE LUCIMAR

MY WIFE LUCIMAR GOMES DA SILVA FLORENTINO

MY WIFE LUCIMAR GOMES DA SILVA FLORENTINO

10_My_FTDNA_MT_DNA_Certificate_A2ab

MY WIFE LUCIMER GOMES DA SILVA FLORENTINO

 

MY WIFE LUCIMAR GOMES DA SILVA FLORENTINO

MY WIFE LUCIMAR GOMES DA SILVA FLORENTINO

Page_1_all-native-american-maps_Lucimar

MY WIFE LUCIMAR GOMES DA SILVA FLORENTINOMY WIFE LUCIMAR GOMES DA SILVA FLORENTINO

MY WIFE LUCIMAR GOMES DA SILVA FLORENTINO

Page_2_all-native-american-maps_Lucimar

MY WIFE LUCIMAR GOMES DA SILVA FLORENTINO

Page_3_all-native-american-maps_Lucimar

MY WIFE LUCIMAR GOMES DA SILVA FLORENTINO

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MY WIFE LUCIMARGOMES DA SILVAFLORENTINO

MY BROTHER IN LAW EDUARDO GOMES DASILVA

MY BROTHER IN LAW EDUARDO GOMES DASILVA

MY BROTHER IN LAW EDUARDO GOMES DA SILVA

MY BROTHER IN LAW EDUARDO GOMES DA SILVA

MY BROTHER IN LAW EDUARDO GOMES DA SILVA

Page_1_all-native-american-maps_Eduardo

MY BROTHER IN LAW EDUARDO GOMES DA SILVA

MY BROTHER IN LAW EDUARDO GOMES DA SILVA

Page_2_all-native-american-maps_Eduardo

MY BROTHER IN LAW EDUARDO GOMES DA SILVA

 

MY BROTHER IN LAW EDUARDO GOMES DA SILVA

MY BROTHER IN LAW EDUARDO GOMES DA SILVA

Page_3_all-native-american-maps_Eduardo

MY BROTHER IN LAW EDUADO GOMES DA SILVA

MY BROTHER IN LAW EDUARDO GOMES DA SILVA

MY BROTHER IN LAW EDUARDO GOMES DA SILVA

Page_4_all-native-american-maps_Eduardo

MY BROTHER EDUARDO GOMES DA SILVA

3_My_FTDNA_MTDNA_Certificate_Alexandre

MY BROTHER IN LAW ALEXANDRE GOMES DA SILVA

Page_1_all-native-american-maps_Alexandre

MY BROTHER IN LAW ALEXANDRE GOMES DA SILVA

Page_2_all-native-american-maps_Alexandre

MY BROTHER IN LAW ALEXANDRE GOMES DA SILVA

Page_3_all-native-american-maps_Alexandre

MY BROTHER IN LAW ALEXANDRE GOMES DA SILVA

Page_4_all-native-american-maps_Alexandre

MY BROTHER IN LAW ALEXANDRE GOMES DA SILVA

3_My_FTDNA_mtDNA_Certificate_Antonio

MY BROTHER IN LAW ANTONIO GOMES DA SILVA

Page_1_all-native-american-maps_Antonio

MY BROTHER IN LAW ANTONIO GOMES DA SILVA

Page_2_all-native-american-maps_Antonio

MY BROTHER IN LAW ANTONIO GOMES DA SILVA

Page_3_all-native-american-maps_Antonio

MY BROTHER IN LAW ANTONIO GOMES DA SILVA

Page_4_all-native-american-maps_Antonio

MY BROTHER IN LAW ANTONIO GOMES DA SILVA

558717_430854247060677_170038640_n

NEPHEW OF MY WIFE PAULO ROBERTO DA ROCHA JUNIOR

10_My_FTDNA_MT_DNA_Paulo_Rocha_Certificate_A2ab

NEPHEW OF MY WIFE PAULO ROBERTO DA ROCHA JUNIOR

NEPHEW OF MY WIFE PAULO ROBERTO DA ROCHA JUNIOR

NEPHEW OF MY WIFE PAULO ROBERTO DA ROCHA JUNIOR

Page_1_all-native-american-maps_Paulo_Rocha

NEPHEW OF MY WIFE PAULO ROBERTO DA ROCHA JUNIOR

NEPHEW OF MY WIFE PAULO ROBERTO DA ROCHA JUNIOR

NEPHEW OF MY WIFE PAULO ROBERTO DA ROCHA JUNIOR

Page_2_all-native-american-maps_Paulo_rocha

NEPHEW OF MY WIFE PAULO ROBERTO DA ROCHA JUNIOR

NEPHEW OF MY WIFE PAULO ROBERTO DA ROCHA JUNIOR

NEPHEW OF MY WIFE PAULO ROBERTO DA ROCHA JUNIOR

Page_3_all-native-american-maps_Paulo_Rocha

NEPHEW OF MY WIFE PAULO ROBERTO DA ROCHA JUNIOR

NEPHEW OF MY WIFE PAULO ROBERTO DA ROCHA JUNIOR

NEPHEW OF MY WIFE PAULO ROBERTO DA ROCHA JUNIOR

Page_4_all-native-american-maps_Paulo_Rocha

NEPHEW OF MY WIFE PAULO ROBERTO DA ROCHA JUNIOR

ALCYNA

MY PATERNAL GRANDMOTHER ALCINA PALMYRA DE JESUS

1_mtDNA_A2_Alcina_Palmyra_de_jesus

MY PATERNAL GRANDMOTHER ALCINA PALMYRA DE JESUS

MY PATERNAN GRANDMOTHER

MY PATERNAN GRANDMOTHER ALCINA PALMYRA DE JESUS

 

MY PATERNAN GRANDMOTHER ALCINA PALMYRA DE JESUS

MY PATERNAN GRANDMOTHER ALCINA PALMYRA DE JESUS

MY PATERNAL GRANDMOTHER ALCINA PALMYRA DE JESUS

MY PATERNAL GRANDMOTHER ALCINA PALMYRA DE JESUS

Page_2_all-native-american-maps_Alcina

MY PATERNAL GRANDMOTHER

MY PATERNAL GRANDMOTHER ALCINA PALMYRA DE JESUS

MY PATERNAL GRANDMOTHER ALCINA PALMYRA DE JESUS

Page_3_all-native-american-maps_Alcina

MY PATERNAL GRANDMOTHER ALCINA PAMYRA DE JESUS

MY PATERNAL GRANDMOTHER ALCINA PALMYRA DE JESUS

MY PATERNAL GRANDMOTHER ALCINA PALMYRA DE JESUS

Page_4_all-native-american-maps_Alcina

MY PATERNAL GRANDMOTHER ALCINA PALMYRA DE JESUS

1_mtDNA_A2_Maria_Jeronyma_de_Jesus

MY PATERNAL GREAT–GRANDMOTHER MARIA JERONYMA DE JESUS

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MY PATERNAL GREAT–GRANDMOTHER MARIA JERONYMA DE JESUS

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MY PATERNAL GREAT–GRANDMOTHER MARIA JERONYMA DE JESUS

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MY PATERNAL GREAT–GRANDMOTHER MARIA JERONYMA DE JESUS

Page_4_all-native-american-maps

MY PATERNAL GREAT–GRANDMOTHER MARIA JERONYMA DE JESUS

1_mtDNA_Maria_Aparecida_Souza

MY PATERNAL COUSIN MARIA APARECIDA DE SOUZA BENEDITO
MY PATERNAL COUSIN MARIA APARECIDA DE SOUZA BENEDITO
MY PATERNAL COUSIN MARIA APARECIDA DE SOUZA BENEDITO

  

 

 

MY PATERNAL COUSIN MARIA APARECIDA DE SOUZA BENEDITO

MY PATERNAL COUSIN MARIA APARECIDA DE SOUZA BENEDITO

Page_2_all-native-american-maps_Eva

MY PATERNAL COUSIN MARIA APARECIDA DE SOUZA BENEDITO

MY PATERNAL COUSIN MARIA APARECIDA DE SOUZA BENEDITO

MY PATERNAL COUSIN MARIA APARECIDA DE SOUZA BENEDITO

Page_3_all-native-american-maps_Aparecida_Sousa

MY PATERNAL COUSIN MARIA APRECIDA DE SOUZA BENEDITO

MY PATERNAL COUSIN MARIA APARECIDA DE SOUZA BENEDITO

MY PATERNAL COUSIN MARIA APARECIDA DE SOUZA BENEDITO

My-Mother

MY MOTHER IN LAW EVA GOMES VIEIRA

10_My_FTDNA_MT_DNA_Certificate_A2ab

MY MOTHER IN LAW EVA GOMES VIEIRA

 

MY MOTHER IN LAW EVA GOMES VIEIRA

MY MOTHER IN LAW EVA GOMES VIEIRA

Page_1_all-native-american-maps_Eva

MY MOTHER IN LAW EVA GOMES VIEIRA

MY MOTHER IN LAW EVA GOMES VIEIRA

MY MOTHER IN LAW EVA GOMES VIEIRA

Page_2_all-native-american-maps_Eva

MY MOTHER IN LAW EVA GOMES VIEIRA

MY MOTHER IN LAW EVA GOMES VIEIRA

MY MOTHER IN LAW EVA GOMES VIEIRA

Page_3_all-native-american-maps_Eva

MY MOTHER IN LAW EVA GOMES VIEIRA

MY MOTHER IN LAW EVA GOMES VIEIRA

MY MOTHER IN LAW EVA GOMES VIEIRA

Page_4_all-native-american-maps_Eva

MY MOTHER IN LAW EVA GOMES VIEIRA

10_My_FTDNA_MT_DNA_Certificate_A2ab

MOTHER OF MY MOTHER IN LAW

Page_1_Native_American_Flausina_Rosalina

Page_2_Native_American_Flausina_Rosalina MOTHER OF MY MOTHER IN LAW

Page_3_Native_American_Flausina_Rosalina

MOTHER OF MY MOTHER IN LAW

Page_4_Native_American_Flausina_Rosalina

MOTHER OF MY MOTHER

10_My_FTDNA_MT_DNA_Certificate_A2ab_Maria_Magdalena

GREAT-GRANDMOTHER OF MY WIFE

Page_1_Native_American_Maria_Magdalena

GREAT-GRANDMOTHER OF MY WIFE

GREAT-GRANDMOTHER OF MY WIFE

GREAT-GRANDMOTHER OF MY WIFE

GREAT-GRANDMOTHER OF MY WIFE

GREAT-GRANDMOTHER OF MY WIFE

Page_4_Native_American_Maria_Magdalena

GREAT-GRANDMOTHER OF MY WIFE

426330_199943780138608_2081982340_n

MY COUSIN PATERNAL JOSÉ MARIO DE SOUZA

1_mtDNA-Haplogroup_A2_José_Mario_Souza_Silva

MY COUSIN PATERNAL OSÉ MARIO DE SOUZA SILVA
MY COUSIN PATERNAL OSÉ MARIO DE SOUZA SILVA

Page_1_all-native-american-maps_José

MY COUSIN PATERNAL JOSÈ MARIO DE SOUZA SILVA

MY COUSIN PATERNAL OSÉ MARIO DE SOUZA SILVA

MY COUSIN PATERNAL OSÉ MARIO DE SOUZA SILVA

Page_2_all-native-american-maps_José

MY COUSIN PATERNAL JOSÉ MARIO DE SOUZA SILVA

MY COUSIN PATERNAL OSÉ MARIO DE SOUZA SILVA

MY COUSIN PATERNAL OSÉ MARIO DE SOUZA SILVA

Page_3_all-native-american-maps_José

MY COUSIN PATERNAL JOSÉ MARIO DE SOUZA SILVA

MY COUSIN PATERNAL OSÉ MARIO DE SOUZA SILVA

MY COUSIN PATERNAL OSÉ MARIO DE SOUZA SILVA

Page_4_all-native-american-maps_José

MY COUSIN PATERNAL

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CERTIFIED FAMILY GENEALOGY GENETICS


 

 

 

CERTIFIED FAMILY GENEALOGY GENETICS (FAMILIAR GENEALOGIA CERTIFICADO GENÉTICA)
1_Certificado_African-Ancestry-Fatima_Igbo

2_Certificate_African_Ancestry_Fatima_Igbo 3-African_Ancestry_Fatima _Y-DNA_E1b1a7a_Bamileke 4_African_Ancestry_Fatima_Y-DNA_E1b1a7a_Bamileke 5_FTDNA_mtDNA_Fatima 6_FTDNA_Y_DNA_SNP_Certificate_Fatima 1_Certificate_African-Ancestry-Maria_Kuiavski_Igbo 2_Certificate_African-Ancestry-Maria_Kuiavski_Igbo 3_Africa_Ancestry_Maria_Kuiavski _Y-DNA_E1b1a7a_Bamileke 4_African_Ancestry_Maria_Kuiavski _Y-DNA_E1b1a7a_Bamileke 4_African_Ancestry_Maria_Kuiavski _Y-DNA_E1b1a7a_Bamileke 5_FTDNA_mtDNA_Maria-Kuiavski 6_My_FTDNA_Y_DNA_SNP_Certificate_Maria_Kuiavski 1_Certificado_African_Ancestry_Lourdes_Igbo 2_Certificate_African_Ancestry_Lourdes_Igbo_1 3_AfricanAncestry_Lourdes _Y-DNA_E1b1a7a_Bamileke 3_AfricanAncestry_Lourdes _Y-DNA_E1b1a7a_Bamileke 4_AfricanAncestry_Lourdes _Y-DNA_E1b1a7a_Bamileke 5_Certificate_FTDNA_mtDNA_Lourdes 6_Certificate_FTDNA_Y_DNA_SNP_Certificate_Lourdes 1_Certificate_African_Ancestry_Daniel_Igbo 2_Certificate_African_Ancestry_Daniel_Igbo 3_AfricanAncestry_Daniel _Y-DNA_Bamileke 4_African_Ancestry_Daniel _Y-DNA_Bamileke 5_FTDNA_mtDNA_Daniel 6_Certificate_FTDNA_Y_DNA_SNP_Certificate_Daniel 7_My_FTDNA_Y_DNA_STR_Certificate 8_Certificate_Y-DNA_December_ 5_2012 8_Certificate_Y-DNA_December_ 5_2012 9_FTDNA_mtDNA_Daniel 1_African_Ancestry_Antonio _Y-DNA_Bamileke 2_African_Ancestry_Antonio _Y-DNA_Bamileke 3_African_Ancestry_Antonio _mtDNA_Igbo 4_Certificate_African_Ancestry_Antonio_Igbo 5_mtDNA_Antonio 6_My_FTDNA_Y_DNA_SNP_Certificate_Antonio 7_Certificate_Y-DNA_December_ 5_2012 7_Certificate_Y-DNA_December_ 5_2012 8_My_FTDNA_Y_DNA_STR_Certificate 1_Certificate_African_Ancestry_Elias_Igbo 2_Certificate_African_Ancestry_Elias_Igbo_1 3_African_Ancestry_Elias_Y-DNA_Bamileke 4_African_Ancestry_Elias _Y-DNA_E1b1a7a_Bamileke 5_Certificate_FTDNA_mtDNA_ELIAS_ 6_FTDNA_Y_DNA_SNP_Certificate_Elias 7_My_FTDNA_Y_DNA_STR_Certificate_Elias 8_Certificate_Y-DNA_December_ 5_2012_Elias 1_African_Ancestry_José_Jorge_Y-DNA__Bamileke 2_African_Ancestry_José_Jorge _Y-DNA_E1b1a7a_Bamileke 3_African_Ancestry_José_Jorge_Igbo 4_Certificate_African_Ancestry_José_Jorge_Igbo 5_mtDNA_José_Jorge 6_FTDNA_Y_DNA_SNP_Certificate_José_Jorge 7_My_FTDNA_Y_DNA_STR_Certificate_Jose_Jorge 8_Certificate_Y-DNA_December_ 5_2012_Jose_Jorge 1_Certificate_African_Ancestry_João_Batista_Igbo 2_African_Ancestry_João_Batista_L2a1c1_Igbo 3_African_Ancestry_João_Batista _Y-DNA_Bamileke 4_African_Ancestry_João _Y-DNA_Bamileke 5_My_FTDNA_Y_DNA_STR_Certificate_João_Batista 6_My_FTDNA_João_Batista_Y_DNA_STR_Certificate 7_My_FTDNA_Y_DNA_STR_Certificate 8_Certificate_Y-DNA_December_ 5_2012 9_My_FTDNA_Y_DNA_SNP_Certificate_João_Batista 10_mtDNA_João_Batista 1_AfricanAncestry_João_Y-DNA_Bamileke 2_AfricanAncestry_João _Y-DNA_Bamilke 4_FTDNA_mtDNA_A2_João_Florentino 5_FTDNA_Y_DNA_SNP_Certificate_João_Florentino 6.1_all-native-american-maps_João 6.3_all-native-american-maps_João 8_Certificate_Y-DNA_December_ 5_2012_João 6.2_all-native-american-maps_João 6.4_all-native-american-maps_João 7_My_FTDNA_Y_DNA_STR_Certificate_João 1_AfricanAncestry_Sarah_Kadosh _mtDNA_L2a1c1_Igbo 2_Certificate_African_Ancestry_Sarah_Kadosh_Igbo mtDNA_Sarah 1_Certificate_African_Ancestry_Olimpia_Maria_Igbo 2_AfricanAncestry_Olimpia_Maria_mtDNA_L2a1c1_Igbo 3_mtDNA_Olimpia_ 1_AfricanAncestry_Maria_Madalena _mtDNA_L2a1c1_Igbo 2_Certificate_African_Ancestry_Maria_Madalena_Igbo 3_mtDNA_Maria_Madalena 1_AfricanAncestry_Ana_Paula _Igbo 2_AfricanAncestry_Ana_Paula _Igbo 3_AfricanAncestry_Antonio _Y-DNA_E1b1a7a_Bamileke 4_AfricanAncestry_Ana_Paula _Igbo 5_Certificate_mtDNA_Ana_paula mtDNA_A2_Alcina_Palmyra_de_jesus mtDNA_A2_Maria_Jeronyma_de_Jesus mtDNA_Maria_Aparecida_Souza mtDNA_Maria_Aparecida_Souza Foto_De_Meu Sogro_Saturnino Meu_Sogro_Saturnino Eu-Geny_ e Meu _Marido_João img057

 

 

 

MY FATHER JOÃO FLORENTINO

MY FATHER JOÃO FLORENTINO

 

GENY DOS SANTOS FLORENTINO

GENY DOS SANTOS FLORENTINO

 

ANTONIO FLORENTINO

ANTONIO FLORENTINO

374230_2571358371591_1045501195_nEUdoc1

MtDNA haplogroup A2 MY WIFE

MtDNA haplogroup A2 MY WIFE

 

MEU PATERNAL HAPLOGROUP Y-DNA E1b1a7a,100% TRIBO BAMILEKE DE CAMARÔES

MEU PATERNAL HAPLOGROUP Y-DNA E1b1a7a,100% TRIBO BAMILEKE DE CAMARÔES

 

Análise MtDNA haplogrupo da minha mãe SARAH KADOSH por DNATribes

Análise MtDNA haplogrupo da minha mãe SARAH KADOSH por DNATribes

 

1234137_214669685363998_818412664_n My_Family ANTONIO-LUCIMAR 7_Fotos_Gabriel_My son 8_Fotos_Gabriel_My son 9_Fotos_Gabriel_My son 10_Fotos_Gabriel_My son 12_Fotos_Gabriel_My son 13_Fotos_Gabriel_My son

My Autossomal Gedmatch Dodecad Project Admixture Oracle results

My Autossomal Gedmatch Dodecad Project Admixture Oracle results

My-Mother 1_mt_migrationmap_FTDNA_Lucimar 2_My_FTDNA_mtDNA_Lucimar_Certificate 5_My_FTDNA_MT_DNA_Certificate_Eva_Gomes 1_My_FTDNA_Y_DNA_SNP_Certificate_Eduardo 2_My_FTDNA_Y_DNA_STR_Certificate_Eduardo 3_My_FTDNA_mtDNA_Certificate_Eduardo 1_My_FTDNA_Y_DNA_SNP_Certificate_Alexandre_Gomesda_Silva 2_My_FTDNA_Y_DNA_STR_Certificate_Alexandre 3_My_FTDNA_MT_DNA_Certificate_Alexandre 1_My_FTDNA_Y_DNA_SNP_Certificate_Antonio_Gomes_da_Silva 2_My_FTDNA_Y_DNA_STR_Certificate_Antonio 3_My_FTDNA_mtDNA_Certificate_Antonio 1_My_FTDNA_Y_DNA_SNP_Certificate_Pedro_Basilio_da_Silva 2_My_FTDNA_Y_DNA_STR_Certificate_Pedro 1_My_FTDNA_Y_DNA_SNP_Certificate_Saturnino_Marques_da_Silva 2_My_FTDNA_Y_DNA_STR_Certificate_Saturnino My_FTDNA_Y_DNA_SNP_Certificate My_FTDNA_Y_DNA_SNP_Certificate_Gomes_Vieira My_FTDNA_Y_DNA_STR_Certificate_Eduardo

Publicado em Uncategorized | 1 Comentário

General History of Africa Collection in Portuguese (PDF only) | United Nations Educational, Scientific and Cultural Organization


General History of Africa Collection in Portuguese (PDF only) | United Nations Educational, Scientific and Cultural Organization.

Publicado em Uncategorized | Deixe um comentário

My Autossomal Gedmatch Harappa Project Admixture OracleResults


My Autossomal Gerdmatch Harappa Project Admixture OracleResults

ANTONIO FLORENTINO

ANTONIO FLORENTINO

My Autossomal Gedmatch Harappa Project Admixture OracleResults

GEDmatch.Com Oracle

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.

My Autossomal HarappaWorld Oracle results:

23 April 2013 – Oracle reference population percentages revised.

Kit F214911

Admix Results (sorted):

# Population Percent
1 W-African 68.8
2 Mediterranean 7.17
3 NE-Euro 6.1
4 E-African 4.85
5 Pygmy 3.88
6 American 3.61
7 San 1.8
8 Caucasian 1.29
9 Baloch 1.15
10 SW-Asian 0.58
11 S-Indian 0.45
12 Beringian 0.33

 

Single Population Sharing:

# Population (source) Distance
1 african-american (1000genomes) 6.71
2 kaba (henn2012) 17.96
3 fang (henn2012) 18.08
4 african-caribbean (1000genomes) 18.66
5 fulani (henn2012) 20.08
6 kongo (henn2012) 20.34
7 bantusouthafrica (hgdp) 20.65
8 pedi (xing) 20.65
9 nguni (xing) 21.63
10 bamoun (henn2012) 22.44
11 bantukenya (hgdp) 25.96
12 mandenka (hgdp) 26.24
13 siddi (reich) 26.71
14 hausa (henn2012) 27.07
15 luhya (hapmap) 27.36
16 luhya (1000genomes) 27.78
17 mada (henn2012) 28.97
18 igbo (henn2012) 29.11
19 bambaran (xing) 29.65
20 brong (henn2012) 30.35

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 62.3% bamoun (henn2012) + 37.7% dominican (bryc) @ 3.11
2 75.4% bamoun (henn2012) + 24.6% puerto-rican (1000genomes) @ 3.26
3 64.6% kongo (henn2012) + 35.4% dominican (bryc) @ 3.53
4 92.8% african-american (1000genomes) + 7.2% sandawe (henn2011) @ 3.89
5 94% african-american (1000genomes) + 6% hadza (henn2011) @ 3.97
6 77.3% kongo (henn2012) + 22.7% puerto-rican (1000genomes) @ 4.08
7 90.2% african-american (1000genomes) + 9.8% hema (xing) @ 4.1
8 89.6% african-american (1000genomes) + 10.4% alur (xing) @ 4.14
9 94.7% african-american (1000genomes) + 5.3% wolayta (pagani) @ 4.21
10 94.5% african-american (1000genomes) + 5.5% maasai (1000genomes) @ 4.23
11 95% african-american (1000genomes) + 5% aricultivator (pagani) @ 4.23
12 94.5% african-american (1000genomes) + 5.5% somali (reich) @ 4.24
13 94.6% african-american (1000genomes) + 5.4% oromo (pagani) @ 4.25
14 95.1% african-american (1000genomes) + 4.9% ariblacksmith (pagani) @ 4.26
15 77% bamoun (henn2012) + 23% colombian (1000genomes) @ 4.28
16 94.8% african-american (1000genomes) + 5.2% esomali (pagani) @ 4.28
17 94.8% african-american (1000genomes) + 5.2% somali (pagani) @ 4.29
18 94.6% african-american (1000genomes) + 5.4% afar (pagani) @ 4.3
19 94.8% african-american (1000genomes) + 5.2% somali (harappa) @ 4.31
20 94.5% african-american (1000genomes) + 5.5% ethiopian (behar) @ 4.31

Gedmatch.Com

My Autossomal HarappaWorld 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

16 components mode.
Component threshold auto-set to 0.760%. Admix results below that value will not be considered.

Kit Number: F214911

Admix Results (sorted):

# Population Percent
1 W-African 69.75
2 Mediterranean 7.27
3 NE-Euro 6.18
4 E-African 4.92
5 Pygmy 3.93
6 American 3.66
7 San 1.82
8 Caucasian 1.30
9 Baloch 1.17

——————————–

Least-squares method.

Using 1 population approximation:
1 african-american @ 6.218
2 fang @ 17.210
3 african-caribbean @ 17.574
4 kaba @ 17.697
5 pedi @ 18.333
6 bantusouthafrica @ 18.389
7 nguni @ 19.332
8 kongo @ 19.443
9 fulani @ 21.468
10 bamoun @ 21.535
377 iterations.

Using 2 populations approximation:
1 50% african-american +50% african-american @ 6.218
2 50% dominican +50% yoruba @ 7.176
3 50% dominican +50% yoruba @ 7.190
4 50% dominican +50% yoruba @ 7.236
5 50% dominican +50% igbo @ 7.485
6 50% dogon +50% dominican @ 7.504
7 50% dominican +50% hausa @ 7.519
8 50% brong +50% dominican @ 7.528
9 50% bambaran +50% dominican @ 7.577
10 50% dominican +50% mandenka @ 8.161
71253 iterations.

Using 3 populations approximation:
1 50% bamoun +25% kaba +25% puerto-rican @ 2.998
2 50% hausa +25% fang +25% puerto-rican @ 3.141
3 50% kongo +25% african-american +25% dominican @ 3.147
4 50% fang +25% hausa +25% puerto-rican @ 3.281
5 50% kongo +25% african-caribbean +25% puerto-rican @ 3.287
6 50% kongo +25% hausa +25% puerto-rican @ 3.327
7 50% kongo +25% hausa +25% puerto-rican @ 3.335
8 50% bamoun +25% hausa +25% puerto-rican @ 3.371
9 50% kongo +25% mandenka +25% puerto-rican @ 3.373
10 50% igbo +25% kaba +25% puerto-rican @ 3.427

435964 iterations.

Using 4 populations approximation:
1 african-american + bamoun + dominican + kaba @ 2.423
2 brong + fang + kaba + puerto-rican @ 2.659
3 african-american + dominican + kaba + kongo @ 2.661
4 fang + kaba + puerto-rican + yoruba @ 2.735
5 fang + kaba + puerto-rican + yoruba @ 2.743
6 fang + igbo + kaba + puerto-rican @ 2.753
7 fang + kaba + puerto-rican + yoruba @ 2.775
8 african-caribbean + bamoun + kaba + puerto-rican @ 2.788
9 igbo + kaba + kongo + puerto-rican @ 2.821
10 bambaran + fang + kaba + puerto-rican @ 2.830
11 brong + kaba + kongo + puerto-rican @ 2.854
12 dogon + fang + kaba + puerto-rican @ 2.869
13 african-american + dominican + fang + kaba @ 2.967
14 bamoun + kaba + puerto-rican + yoruba @ 2.974
15 bamoun + igbo + kaba + puerto-rican @ 2.984
16 bamoun + kaba + puerto-rican + yoruba @ 2.991
17 bambaran + kaba + kongo + puerto-rican @ 2.994
18 bamoun + bamoun + kaba + puerto-rican @ 2.998
19 african-caribbean + igbo + kaba + puerto-rican @ 3.010
20 bamoun + brong + kaba + puerto-rican @ 3.015

18404227 iterations.

Done.

Elapsed time 12.4326 seconds.

Gedmatch.Com

My Autossomal HarappaWorld 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. 377 populations found.
16 population clusters.

Kit Number: F214911

Admix Results:

# Population Percent
1 S-Indian 0.45
2 Baloch 1.15
3 Caucasian 1.29
4 NE-Euro 6.10
5 SE-Asian 0.00
6 Siberian 0.00
7 NE-Asian 0.00
8 Papuan 0.00
9 American 3.61
10 Beringian 0.33
11 Mediterranean 7.17
12 SW-Asian 0.58
13 San 1.80
14 E-African 4.85
15 Pygmy 3.88
16 W-African 68.80

Pct. Calc. Option 2

1 african-american 64.93%
2 brong 15.58%
3 aricultivator 5.17%
4 biakapygmy 3.70%
5 surui 3.63%
6 bantusouthafrica 3.44%
7 sardinian 2.25%
8 tunisia 1.09%
9 dominican 0.20%
10 colombian 0.01%

Total RMSD: 0.798651

Elapsed time 0.7343 seconds.

Publicado em My Autossomal Harappa Project Admixture OracleResults | 2 Comentários

My Autossomal Gedmatch Dodecad Project Admixture Oracle results


My Autossomal Gedmatch Dodecad Project Admixture Oracle results

ANTONIO FLORENTINO

ANTONIO FLORENTINO

My Autossomal Gedmatch Dodecad Project Admixture Oracle results

My Autossomal Dodecad Project Admixture Oracle results

GEDmatch.Com Oracle

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.

My Autossomal Dodecad V3 Oracle results:

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

Kit F214911

Admix Results (sorted):

# Population Percent
1 Neo_African 44.97
2 Palaeo_African 26.34
3 East_African 9.03
4 West_European 6.92
5 East_European 3.19
6 Northwest_African 2.91
7 Mediterranean 2.49
8 Northeast_Asian 1.73
9 West_Asian 0.93
10 Southeast_Asian 0.81
11 South_Asian 0.67

Single Population Sharing:

# Population (source) Distance
1 ASW (HapMap) 4.83
2 Luhya (Henn) 14.79
3 Luhya (Xing) 14.88
4 LWK (HapMap) 15.34
5 Mada (Henn) 15.82
6 Kaba (Henn) 16.66
7 Hausa (Henn) 18.41
8 Kongo (Henn) 18.51
9 Bamoun (Henn) 18.99
10 Fang (Henn) 19.14
11 Pedi (Xing) 19.25
12 Nguni (Xing) 19.41
13 Brong (Henn) 19.6
14 Igbo (Henn) 19.91
15 Fulani (Henn) 20.04
16 Alur (Xing) 20.63
17 Siddi (Reich) 21.84
18 Bambaran (Xing) 21.86
19 Xhosa (Henn) 22.57
20 Hema (Xing) 23.3

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 90.7% ASW (HapMap) + 9.3% SANDAWE (Henn) @ 3.52
2 87.5% ASW (HapMap) + 12.5% Hema (Xing) @ 3.53
3 92.9% ASW (HapMap) + 7.1% HADZA (Henn) @ 3.63
4 87.1% ASW (HapMap) + 12.9% Alur (Xing) @ 3.78
5 93.6% ASW (HapMap) + 6.4% Maasai (Henn) @ 3.88
6 94.3% ASW (HapMap) + 5.7% MKK (HapMap) @ 3.96
7 89.9% ASW (HapMap) + 10.1% Bulala (Henn) @ 4.05
8 85.2% ASW (HapMap) + 14.8% Luhya (Xing) @ 4.15
9 96.6% ASW (HapMap) + 3.4% Ethiopians (Behar) @ 4.15
10 89.7% ASW (HapMap) + 10.3% Siddi (Reich) @ 4.15
11 96.7% ASW (HapMap) + 3.3% East_African (Dodecad) @ 4.17
12 96.7% ASW (HapMap) + 3.3% Ethiopian_Jews (Behar) @ 4.17
13 89.5% ASW (HapMap) + 10.5% Fulani (Henn) @ 4.25
14 86.4% ASW (HapMap) + 13.6% Luhya (Henn) @ 4.29
15 96.5% ASW (HapMap) + 3.5% !Kung (Xing) @ 4.34
16 96.9% ASW (HapMap) + 3.1% SAN_SA (Henn) @ 4.35
17 97.6% ASW (HapMap) + 2.4% Mozabite (HGDP) @ 4.36
18 98% ASW (HapMap) + 2% San (HGDP) @ 4.37
19 88.1% ASW (HapMap) + 11.9% Mada (Henn) @ 4.38
20 98% ASW (HapMap) + 2% Evenk_15 (Rasmussen) @ 4.39

 

GEDmatch.Com Oracle

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.
Gedmatch.Com

My Autossomal 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.

Revised: Dec 6, 2012

12 components mode.
Component threshold auto-set to 1.010%. Admix results below that value will not be considered.

Kit Number: F214911

Admix Results (sorted):

# Population Percent
1 Neo_African 46.08
2 Palaeo_African 26.99
3 East_African 9.26
4 West_European 7.10
5 East_European 3.26
6 Northwest_African 2.98
7 Mediterranean 2.56
8 Northeast_Asian 1.78

——————————–

Least-squares method.

Using 1 population approximation:
1 ASW @ 4.952
2 LWK @ 13.563
3 Luhya @ 13.663
4 Luhya @ 13.716
5 Kaba @ 14.327
6 Kongo @ 15.187
7 Mada @ 15.413
8 Pedi @ 15.417
9 Hausa @ 15.464
10 Fang @ 15.551
227 iterations.

Using 2 populations approximation:
1 50% ASW +50% ASW @ 4.952
2 50% ASW +50% Luhya @ 6.061
3 50% ASW +50% Luhya @ 6.151
4 50% ASW +50% LWK @ 6.203
5 50% ASW +50% Kaba @ 6.933
6 50% ASW +50% Mada @ 7.095
7 50% ASW +50% Pedi @ 7.168
8 50% ASW +50% Nguni @ 7.273
9 50% ASW +50% Kongo @ 7.419
10 50% ASW +50% Fang @ 7.540
25878 iterations.

Using 3 populations approximation:
1 50% ASW +25% ASW +25% Luhya @ 3.637
2 50% ASW +25% ASW +25% Luhya @ 3.774
3 50% ASW +25% ASW +25% LWK @ 3.880
4 50% ASW +25% ASW +25% Alur @ 4.044
5 50% ASW +25% ASW +25% Mada @ 4.153
6 50% ASW +25% Fulani +25% Nguni @ 4.238
7 50% ASW +25% ASW +25% Pedi @ 4.245
8 50% ASW +25% Fulani +25% Pedi @ 4.252
9 50% ASW +25% ASW +25% Nguni @ 4.278
10 50% ASW +25% Fulani +25% Xhosa @ 4.392
362863 iterations.

Using 4 populations approximation:
1 ASW + ASW + ASW + Luhya @ 3.637
2 ASW + ASW + ASW + Luhya @ 3.774
3 ASW + ASW + ASW + LWK @ 3.880
4 ASW + ASW + ASW + Alur @ 4.044
5 ASW + ASW + ASW + Mada @ 4.153
6 ASW + ASW + Fulani + Nguni @ 4.238
7 ASW + ASW + ASW + Pedi @ 4.245
8 ASW + ASW + Fulani + Pedi @ 4.252
9 ASW + ASW + ASW + Nguni @ 4.278
10 ASW + ASW + Fulani + Xhosa @ 4.392
11 ASW + ASW + ASW + Kaba @ 4.426
12 ASW + ASW + Fang + Fulani @ 4.485
13 ASW + ASW + Fulani + Sotho_Tswana @ 4.515
14 ASW + ASW + Fulani + Kongo @ 4.598
15 ASW + ASW + ASW + Fang @ 4.649
16 ASW + ASW + ASW + Kongo @ 4.653
17 ASW + ASW + LWK + Fulani @ 4.786
18 ASW + ASW + Bamoun + Fulani @ 4.807
19 ASW + ASW + ASW + Bamoun @ 4.883
20 ASW + ASW + ASW + Sotho_Tswana @ 4.916

2548488 iterations.

Done.

Elapsed time 1.6105 seconds.

Gedmatch.Com

My Autossomal Dodecad V3 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. 227 populations found.
12 population clusters.

Kit Number: F214911

Admix Results:

# Population Percent
1 East_European 3.19
2 West_European 6.92
3 Mediterranean 2.49
4 Neo_African 44.97
5 West_Asian 0.93
6 South_Asian 0.67
7 Northeast_Asian 1.73
8 Southeast_Asian 0.81
9 East_African 9.03
10 Southwest_Asian 0.00
11 Northwest_African 2.91
12 Palaeo_African 26.34

Pct. Calc. Option 2

1 ASW 58.78%
2 Kongo 15.78%
3 HADZA 7.18%
4 Mandenka 6.31%
5 Mozabite 4.97%
6 Chuvashs_16 4.84%
7 Bulala 2.00%
8 Evenk_15 0.12%
9 Siddi 0.02%
10 Lithuanian 0.00%

Total RMSD: 0.728527

Elapsed time 0.5321 seconds.
Many thanks also to Zack Ajmal for helping us get this web version of Dienekes’ Oracle program developed.

My Autossomal Africa9 Oracle results:

Kit F214911

Admix Results (sorted):

# Population Percent
1 W_Africa 46.32
2 Europe 12.67
3 S_Africa 11.1
4 Biaka 11.05
5 E_Africa 7.37
6 NW_Africa 5.68
7 SW_Asia 3.38
8 San 2.44

Single Population Sharing:

# Population (source) Distance
1 Fang 20.63
2 Luhya 22.83
3 Kongo 23.49
4 Bamoun 24.76
5 Bantu_N.E. 25.17
6 Kaba 28.3
7 Mada 30.66
8 Hausa 30.68
9 Igbo 31.85
10 Yoruba 33.13
11 Fulani 34.37
12 Brong 35.39
13 Bulala 39.48
14 Mandenka 40.4
15 Morocco_S 53.98
16 Maasai 54.42
17 Algeria 58.15
18 Libya 59.18
19 North_African (Dodecad) 59.36
20 HADZA 61.08

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 81% Fang + 19% North_Italian @ 7.28
2 80.7% Fang + 19.3% Tuscan @ 7.63
3 78.5% Fang + 21.5% Morocco_Jews @ 7.83
4 79.2% Fang + 20.8% North_African_Jews (Dodecad) @ 9.16
5 84.9% Fang + 15.1% French_Basque @ 9.34
6 79.3% Kongo + 20.7% North_Italian @ 9.87
7 76.6% Kongo + 23.4% Morocco_Jews @ 9.96
8 76.4% Fang + 23.6% North_African (Dodecad) @ 9.99
9 79.1% Kongo + 20.9% Tuscan @ 10.12
10 75.5% Bamoun + 24.5% Morocco_Jews @ 10.33
11 78.5% Bamoun + 21.5% North_Italian @ 10.61
12 78.2% Bamoun + 21.8% Tuscan @ 10.8
13 77.3% Kongo + 22.7% North_African_Jews (Dodecad) @ 11.11
14 81.5% Fang + 18.5% Druze @ 11.36
15 76.2% Bamoun + 23.8% North_African_Jews (Dodecad) @ 11.45
16 74% Kongo + 26% North_African (Dodecad) @ 11.5
17 72.7% Bamoun + 27.3% North_African (Dodecad) @ 11.58
18 77.1% Fang + 22.9% Algeria @ 11.76
19 79.2% Fang + 20.8% Morocco_N @ 11.79
20 78.7% Fang + 21.3% Egypt @ 11.8

Gedmatch.Com

My Autossomal 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: F214911

Admix Results (sorted):

# Population Percent
1 W_Africa 46.32
2 Europe 12.67
3 S_Africa 11.10
4 Biaka 11.05
5 E_Africa 7.37
6 NW_Africa 5.68
7 SW_Asia 3.38
8 San 2.44

——————————–

Least-squares method.

Using 1 population approximation:
1 Fang @ 21.071
2 Luhya @ 23.837
3 Kongo @ 24.372
4 Bamoun @ 26.249
5 Bantu_N.E. @ 26.545
6 Kaba @ 30.313
7 Bantu_S.E._Pedi @ 31.588
8 Mada @ 32.940
9 Hausa @ 33.320
10 Igbo @ 34.663
54 iterations.

Using 2 populations approximation:
1 50% Fang +50% Luhya @ 18.427
2 50% Bantu_N.E. +50% Fang @ 18.868
3 50% Kongo +50% Luhya @ 20.099
4 50% Bamoun +50% Luhya @ 20.381
5 50% Bantu_N.E. +50% Kongo @ 20.703
6 50% Bamoun +50% Bantu_N.E. @ 20.877
7 50% Fulani +50% Luhya @ 20.920
8 50% Fang +50% Fang @ 21.071
9 50% Bantu_S.E._Pedi +50% Luhya @ 21.386
10 50% Bantu_S.E._Pedi +50% Fang @ 21.401
1485 iterations.

Using 3 populations approximation:
1 50% Fang +25% Kaba +25% Morocco_Jews @ 8.242
2 50% Fang +25% Mada +25% Morocco_Jews @ 8.376
3 50% Fang +25% Fang +25% Morocco_Jews @ 8.398
4 50% Fang +25% Kongo +25% Morocco_Jews @ 8.503
5 50% Fang +25% Bamoun +25% Morocco_Jews @ 8.526
6 50% Fang +25% Luhya +25% Morocco_Jews @ 8.688
7 50% Fang +25% Hausa +25% Morocco_Jews @ 8.951
8 50% Bamoun +25% Luhya +25% Morocco_Jews @ 8.990
9 50% Fang +25% Bantu_N.E. +25% Morocco_Jews @ 9.084
10 50% Kongo +25% Fang +25% Morocco_Jews @ 9.119
37561 iterations.

Using 4 populations approximation:
1 Fang + Fang + Kaba + Morocco_Jews @ 8.242
2 Fang + Fang + Mada + Morocco_Jews @ 8.376
3 Fang + Fang + Fang + Morocco_Jews @ 8.398
4 Bamoun + Fang + Luhya + Morocco_Jews @ 8.489
5 Fang + Fang + Kongo + Morocco_Jews @ 8.503
6 Bamoun + Fang + Fang + Morocco_Jews @ 8.526
7 Fang + Fang + Luhya + Morocco_Jews @ 8.688
8 Fang + Kongo + Mada + Morocco_Jews @ 8.871
9 Fang + Kongo + Luhya + Morocco_Jews @ 8.896
10 Fang + Luhya + Morocco_Jews + Yoruba @ 8.900
11 Fang + Igbo + Luhya + Morocco_Jews @ 8.928
12 Fang + Hausa + Luhya + Morocco_Jews @ 8.942
13 Bamoun + Bantu_N.E. + Fang + Morocco_Jews @ 8.951
14 Fang + Fang + Hausa + Morocco_Jews @ 8.951
15 Bamoun + Bamoun + Luhya + Morocco_Jews @ 8.990
16 Fang + Kaba + Kongo + Morocco_Jews @ 9.049
17 Bantu_N.E. + Fang + Fang + Morocco_Jews @ 9.084
18 Fang + Kongo + Kongo + Morocco_Jews @ 9.119
19 Bamoun + Fang + Kongo + Morocco_Jews @ 9.128
20 Fang + Fang + Kaba + North_Italian @ 9.148

81249 iterations.

Done.

Elapsed time 0.0507 seconds.

Gedmatch.Com

My Autossomal 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: F214911

Admix Results:

# Population Percent
1 Europe 12.67
2 NW_Africa 5.68
3 SW_Asia 3.38
4 E_Africa 7.37
5 S_Africa 11.10
6 Mbuti 0.00
7 W_Africa 46.32
8 Biaka 11.05
9 San 2.44

Pct. Calc. Option 2

0 Unable to determine 0.02%
1 Hausa 40.56%
2 North_Italian 13.90%
3 Mandenka 11.83%
4 SANDAWE 8.54%
5 Biaka_Pygmies 8.02%
6 Bantu_S.E._Tswana 6.11%
7 Mozabite 5.67%
8 Fulani 4.27%
9 French_Basque 1.08%
10 Morocco_S 0.00%

Total RMSD: 1.191497

Elapsed time 0.4241 seconds.

GEDmatch.Com Oracle

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.

My Autossomal World9 Oracle results:

Kit F214911

Admix Results (sorted):

# Population Percent
1 African 77.24
2 Atlantic_Baltic 10.96
3 Southern 6.44
4 Amerindian 4.02
5 Caucasus_Gedrosia 0.74
6 South_Asian 0.47
7 Siberian 0.13

Single Population Sharing:

# Population (source) Distance
1 ASW30 (HapMap3) 6.42
2 San_He 13.72
3 ACB30 14.54
4 Hadza_He 14.87
5 Sandawe_He 16.92
6 MKK30 (Dodecad) 20.34
7 Bantu_N.E. (HGDP) 21
8 LWK30 (Behar) 21.85
9 Mandenka 24.67
10 Bantu_S.W._Herero (HGDP) 27.45
11 YRI30 (HGDP) 27.84
12 San 27.92
13 Yoruba (HGDP) 28.33
14 Bantu_S.E._Tswana (HGDP) 28.37
15 Biaka_Pygmies 29.08
16 Mbuti_Pygmies 29.08
17 Dominican 46.3
18 Somali (Dodecad) 48.55
19 Ethiopians (Behar) 52.89
20 Ethiopian_Jews (Behar) 55.7

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 71.3% Yoruba (HGDP) + 28.7% Puerto_Rican @ 0.8
2 71.7% YRI30 (HGDP) + 28.3% Puerto_Rican @ 0.85
3 71.3% Bantu_S.E._Tswana (HGDP) + 28.7% Puerto_Rican @ 0.85
4 70.8% Biaka_Pygmies + 29.2% Puerto_Rican @ 0.87
5 70.8% Mbuti_Pygmies + 29.2% Puerto_Rican @ 0.87
6 74.3% YRI30 (HGDP) + 25.7% PUR30 @ 1.05
7 72% Bantu_S.W._Herero (HGDP) + 28% Puerto_Rican @ 1.05
8 73.9% Yoruba (HGDP) + 26.1% PUR30 @ 1.06
9 73.9% Bantu_S.E._Tswana (HGDP) + 26.1% PUR30 @ 1.12
10 62.1% Yoruba (HGDP) + 37.9% Dominican @ 1.18
11 62.5% YRI30 (HGDP) + 37.5% Dominican @ 1.19
12 73.4% Biaka_Pygmies + 26.6% PUR30 @ 1.19
13 73.4% Mbuti_Pygmies + 26.6% PUR30 @ 1.19
14 62% Bantu_S.E._Tswana (HGDP) + 38% Dominican @ 1.2
15 74.5% Bantu_S.W._Herero (HGDP) + 25.5% PUR30 @ 1.22
16 61.4% Biaka_Pygmies + 38.6% Dominican @ 1.23
17 61.4% Mbuti_Pygmies + 38.6% Dominican @ 1.23
18 62.8% Bantu_S.W._Herero (HGDP) + 37.2% Dominican @ 1.27
19 86% ACB30 + 14% CLM30 @ 1.35
20 71.6% San + 28.4% Puerto_Rican @ 1.53

Gedmatch.Com

My Autossomal World9 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: F214911

Admix Results (sorted):

# Population Percent
1 African 78.29
2 Atlantic_Baltic 11.11
3 Southern 6.52
4 Amerindian 4.08

——————————–

Least-squares method.

Using 1 population approximation:
1 ASW30 @ 5.504
2 ACB30 @ 12.378
3 San_He @ 12.662
4 Hadza_He @ 14.595
5 Sandawe_He @ 18.155
6 Bantu_N.E. @ 18.777
7 LWK30 @ 19.461
8 MKK30 @ 21.643
9 Mandenka @ 21.768
10 Bantu_S.W._Herero @ 24.190
250 iterations.

Using 2 populations approximation:
1 50% ASW30 +50% ASW30 @ 5.504
2 50% ASW30 +50% Hadza_He @ 8.182
3 50% ASW30 +50% ACB30 @ 8.342
4 50% ASW30 +50% Sandawe_He @ 8.386
5 50% ASW30 +50% San_He @ 8.499
6 50% Bantu_S.E._Pedi +50% Dominican @ 8.956
7 50% Bantu_S.E._S.Sotho +50% Dominican @ 8.956
8 50% Biaka_Pygmies +50% Dominican @ 8.956
9 50% Mbuti_Pygmies +50% Dominican @ 8.956
10 50% Bantu_S.E._Tswana +50% Dominican @ 9.252
31375 iterations.

Using 3 populations approximation:
1 50% YRI30 +25% Yoruba +25% PUR30 @ 1.716
2 50% Bantu_S.W._Ovambo +25% Yoruba +25% PUR30 @ 1.716
3 50% Bantu_S.W._Ovambo +25% Bantu_S.W._Ovambo +25% PUR30 @ 1.717
4 50% Bantu_S.W._Ovambo +25% YRI30 +25% PUR30 @ 1.719
5 50% Yoruba +25% YRI30 +25% PUR30 @ 1.719
6 50% YRI30 +25% Bantu_S.W._Ovambo +25% PUR30 @ 1.721
7 50% Yoruba +25% Bantu_S.W._Ovambo +25% PUR30 @ 1.722
8 50% YRI30 +25% YRI30 +25% PUR30 @ 1.725
9 50% YRI30 +25% Bantu_S.E._Pedi +25% PUR30 @ 1.725
10 50% YRI30 +25% Bantu_S.E._S.Sotho +25% PUR30 @ 1.725

1160472 iterations.

Using 4 populations approximation:
1 Bantu_S.W._Ovambo + Yoruba + YRI30 + PUR30 @ 1.716
2 Yoruba + YRI30 + YRI30 + PUR30 @ 1.716
3 Bantu_S.W._Ovambo + Bantu_S.W._Ovambo + Yoruba + PUR30 @ 1.716
4 Bantu_S.W._Ovambo + Bantu_S.W._Ovambo + Bantu_S.W._Ovambo + PUR30 @ 1.717
5 Bantu_S.W._Ovambo + Bantu_S.W._Ovambo + YRI30 + PUR30 @ 1.719
6 Yoruba + Yoruba + YRI30 + PUR30 @ 1.719
7 Bantu_S.W._Ovambo + YRI30 + YRI30 + PUR30 @ 1.721
8 Bantu_S.W._Ovambo + Yoruba + Yoruba + PUR30 @ 1.722
9 YRI30 + YRI30 + YRI30 + PUR30 @ 1.725
10 Bantu_S.E._Pedi + YRI30 + YRI30 + PUR30 @ 1.725
11 Bantu_S.E._S.Sotho + YRI30 + YRI30 + PUR30 @ 1.725
12 Biaka_Pygmies + YRI30 + YRI30 + PUR30 @ 1.725
13 Mbuti_Pygmies + YRI30 + YRI30 + PUR30 @ 1.725
14 Bantu_S.E._Tswana + YRI30 + YRI30 + PUR30 @ 1.728
15 Bantu_S.E._Tswana + Bantu_S.W._Ovambo + YRI30 + PUR30 @ 1.728
16 Bantu_S.E._Tswana + Bantu_S.W._Ovambo + Bantu_S.W._Ovambo + PUR30 @ 1.729
17 Bantu_S.E._Pedi + Bantu_S.W._Ovambo + YRI30 + PUR30 @ 1.729
18 Bantu_S.E._S.Sotho + Bantu_S.W._Ovambo + YRI30 + PUR30 @ 1.729
19 Bantu_S.W._Ovambo + Biaka_Pygmies + YRI30 + PUR30 @ 1.729
20 Bantu_S.W._Ovambo + Mbuti_Pygmies + YRI30 + PUR30 @ 1.729

3857174 iterations.

Done.

Elapsed time 2.2140 seconds.

Gedmatch.Com

My Autossomal World9 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. 250 populations found.
9 population clusters.

Kit Number: F214911

Admix Results:

# Population Percent
1 Amerindian 4.02
2 East_Asian 0.00
3 African 77.24
4 Atlantic_Baltic 10.96
5 Australasian 0.00
6 Siberian 0.13
7 Caucasus_Gedrosia 0.74
8 Southern 6.44
9 South_Asian 0.47

Pct. Calc. Option 2

1 ASW30 74.30%
2 Hadza_He 9.30%
3 PEL30 6.56%
4 San_He 5.06%
5 Ethiopian_Jews 2.04%
6 Somali 1.59%
7 Dominican 1.12%
8 Yemen_Jews 0.01%
9 Moroccans 0.01%
10 Ethiopians 0.00%

Total RMSD: 1.093583

Elapsed time 0.7418 seconds.

GEDmatch.Com Oracle

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.

My Autossomal Dodecad K7b Oracle results:

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

Kit F214911

Admix Results (sorted):

# Population Percent
1 African 78.47
2 Atlantic_Baltic 11.98
3 Southern 4.4
4 West_Asian 2.22
5 Siberian 1.53
6 East_Asian 1.23
7 South_Asian 0.18

Single Population Sharing:

# Population (source) Distance
1 ASW30 (HapMap3) 9.04
2 Sandawe (Henn) 18.04
3 MKK30 (Dodecad) 21.32
4 LWK30 (Behar) 24.44
5 Bantu_N.E. (HGDP) 25.46
6 Mandenka (HGDP) 27.93
7 Bantu_S.E._Tswana (HGDP) 28.33
8 Bantu_S.W._Herero (HGDP) 28.5
9 Yoruba (HGDP) 28.97
10 YRI30 (HGDP) 28.97
11 Somali (Dodecad) 49.39
12 Ethiopian_Jews (Behar) 60.17
13 Ethiopians (Behar) 61.66
14 Moroccans (Behar) 85.19
15 Algerian (Dodecad) 86.73
16 Mozabite (HGDP) 86.88
17 Yemenese (Behar) 90.17
18 Egyptans (Behar) 90.65
19 Moroccan (Dodecad) 90.8
20 Palestinian (HGDP) 101.82

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 82.1% LWK30 (Behar) + 17.9% Mordovians (Yunusbayev) @ 2.03
2 81.3% Bantu_N.E. (HGDP) + 18.7% Hungarians (Behar) @ 2.06
3 82.2% LWK30 (Behar) + 17.8% Mixed_Slav (Dodecad) @ 2.15
4 81.9% LWK30 (Behar) + 18.1% Hungarians (Behar) @ 2.17
5 82.2% LWK30 (Behar) + 17.8% Ukranians (Yunusbayev) @ 2.2
6 82.3% LWK30 (Behar) + 17.7% Russian_B (Behar) @ 2.3
7 82.2% LWK30 (Behar) + 17.8% Russian (HGDP) @ 2.31
8 90.8% ASW30 (HapMap3) + 9.2% Algerian (Dodecad) @ 2.32
9 92.2% ASW30 (HapMap3) + 7.8% Morocco_Jews (Behar) @ 2.34
10 92.3% ASW30 (HapMap3) + 7.7% Sephardic_Jews (Behar) @ 2.43
11 92.2% ASW30 (HapMap3) + 7.8% Bedouin (HGDP) @ 2.47
12 91.2% ASW30 (HapMap3) + 8.8% Egyptans (Behar) @ 2.47
13 82.2% LWK30 (Behar) + 17.8% German (Dodecad) @ 2.49
14 82.2% LWK30 (Behar) + 17.8% Dutch (Dodecad) @ 2.53
15 82.2% LWK30 (Behar) + 17.8% Mixed_Germanic (Dodecad) @ 2.55
16 79.2% Bantu_S.E._Tswana (HGDP) + 20.8% N_Italian (Dodecad) @ 2.57
17 79% Bantu_S.E._Tswana (HGDP) + 21% Romanians (Behar) @ 2.59
18 92.4% ASW30 (HapMap3) + 7.6% Ashkenazi (Dodecad) @ 2.59
19 92.2% ASW30 (HapMap3) + 7.8% Palestinian (HGDP) @ 2.6
20 81.4% Bantu_N.E. (HGDP) + 18.6% French (HGDP) @ 2.61

Gedmatch.Com

My Autossomal Dodecad K7b 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

7 components mode.
Component threshold auto-set to 1.720%. Admix results below that value will not be considered.

Kit Number: F214911

Admix Results (sorted):

# Population Percent
1 African 80.85
2 Atlantic_Baltic 12.34
3 Southern 4.53
4 West_Asian 2.29

——————————–

Least-squares method.

Using 1 population approximation:
1 ASW30 @ 5.718
2 Sandawe @ 19.360
3 LWK30 @ 19.856
4 Bantu_N.E. @ 20.625
5 Mandenka @ 22.471
6 MKK30 @ 22.794
7 Bantu_S.E._Tswana @ 22.829
8 Bantu_S.W._Herero @ 22.998
9 Bantu_S.E._Zulu @ 23.100
10 Bantu_S.E._Pedi @ 23.343
223 iterations.

Using 2 populations approximation:
1 50% ASW30 +50% ASW30 @ 5.718
2 50% ASW30 +50% Sandawe @ 8.538
3 50% ASW30 +50% MKK30 @ 9.736
4 50% ASW30 +50% LWK30 @ 12.008
5 50% ASW30 +50% Bantu_N.E. @ 12.473
6 50% ASW30 +50% Mandenka @ 13.551
7 50% ASW30 +50% Bantu_S.E._Tswana @ 13.765
8 50% ASW30 +50% Bantu_S.W._Herero @ 13.841
9 50% ASW30 +50% Bantu_S.E._Zulu @ 13.893
10 50% ASW30 +50% Bantu_S.E._Pedi @ 14.017
24976 iterations.

Using 3 populations approximation:
1 50% ASW30 +25% ASW30 +25% MKK30 @ 4.291
2 50% ASW30 +25% ASW30 +25% Sandawe @ 4.482
3 50% ASW30 +25% ASW30 +25% ASW30 @ 5.718
4 50% Bantu_S.E._Pedi +25% Bantu_S.E._Pedi +25% Canarias @ 6.397
5 50% Bantu_S.E._Pedi +25% Bantu_S.E._S.Sotho +25% Canarias @ 6.397
6 50% Bantu_S.E._Pedi +25% Bantu_S.W._Ovambo +25% Canarias @ 6.397
7 50% Bantu_S.E._Pedi +25% Canarias +25% Yoruba @ 6.397
8 50% Bantu_S.E._Pedi +25% Canarias +25% YRI30 @ 6.397
9 50% Bantu_S.E._S.Sotho +25% Bantu_S.E._Pedi +25% Canarias @ 6.397
10 50% Bantu_S.E._S.Sotho +25% Bantu_S.E._S.Sotho +25% Canarias @ 6.397
609481 iterations.

Using 4 populations approximation:
1 ASW30 + ASW30 + ASW30 + MKK30 @ 4.291
2 ASW30 + ASW30 + ASW30 + Sandawe @ 4.482
3 ASW30 + ASW30 + ASW30 + ASW30 @ 5.718
4 Bantu_S.E._Pedi + Bantu_S.E._Pedi + Bantu_S.E._Pedi + Canarias @ 6.397
5 Bantu_S.E._Pedi + Bantu_S.E._Pedi + Bantu_S.E._S.Sotho + Canarias @ 6.397
6 Bantu_S.E._Pedi + Bantu_S.E._Pedi + Bantu_S.W._Ovambo + Canarias @ 6.397
7 Bantu_S.E._Pedi + Bantu_S.E._Pedi + Canarias + Yoruba @ 6.397
8 Bantu_S.E._Pedi + Bantu_S.E._Pedi + Canarias + YRI30 @ 6.397
9 Bantu_S.E._Pedi + Bantu_S.E._S.Sotho + Bantu_S.E._S.Sotho + Canarias @ 6.397
10 Bantu_S.E._Pedi + Bantu_S.E._S.Sotho + Bantu_S.W._Ovambo + Canarias @ 6.397
11 Bantu_S.E._Pedi + Bantu_S.E._S.Sotho + Canarias + Yoruba @ 6.397
12 Bantu_S.E._Pedi + Bantu_S.E._S.Sotho + Canarias + YRI30 @ 6.397
13 Bantu_S.E._Pedi + Bantu_S.W._Ovambo + Bantu_S.W._Ovambo + Canarias @ 6.397
14 Bantu_S.E._Pedi + Bantu_S.W._Ovambo + Canarias + Yoruba @ 6.397
15 Bantu_S.E._Pedi + Bantu_S.W._Ovambo + Canarias + YRI30 @ 6.397
16 Bantu_S.E._Pedi + Canarias + Yoruba + Yoruba @ 6.397
17 Bantu_S.E._Pedi + Canarias + Yoruba + YRI30 @ 6.397
18 Bantu_S.E._Pedi + Canarias + YRI30 + YRI30 @ 6.397
19 Bantu_S.E._S.Sotho + Bantu_S.E._S.Sotho + Bantu_S.E._S.Sotho + Canarias @ 6.397
20 Bantu_S.E._S.Sotho + Bantu_S.E._S.Sotho + Bantu_S.W._Ovambo + Canarias @ 6.397

1998900 iterations.

Done.

Elapsed time 1.0711 seconds.

Gedmatch.Com

My Autossomal Dodecad K7b 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. 223 populations found.
7 population clusters.

Kit Number: F214911

Admix Results:

# Population Percent
1 South_Asian 0.18
2 West_Asian 2.22
3 Siberian 1.53
4 African 78.47
5 Southern 4.40
6 Atlantic_Baltic 11.98
7 East_Asian 1.23

Pct. Calc. Option 2

0 Unable to determine 0.02%
1 ASW30 74.49%
2 Samaritians 8.60%
3 Bantu_S.E._Zulu 4.81%
4 Bantu_S.E._Tswana 4.63%
5 Bantu_S.E._S.Sotho 4.18%
6 FIN30 1.97%
7 Oroqen 1.06%
8 Hezhen 0.12%
9 Daur 0.12%
10 Finnish 0.01%

Total RMSD: 1.301926

Elapsed time 0.3573 seconds.

GEDmatch.Com Oracle

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.

My Autossomal Dodecad K12b Oracle results:

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

Kit F214911

Admix Results (sorted):

# Population Percent
1 Sub_Saharan 70.55
2 East_African 9.1
3 North_European 6.97
4 Atlantic_Med 5.53
5 Caucasus 2.01
6 Northwest_African 1.59
7 East_Asian 1.28
8 Siberian 1.26
9 Gedrosia 0.95
10 Southwest_Asian 0.36
11 South_Asian 0.21
12 Southeast_Asian 0.17

Single Population Sharing:

# Population (source) Distance
1 ASW30 (HapMap3) 18.19
2 Bantu_N.E. (HGDP) 19.04
3 LWK30 (Behar) 19.73
4 Bantu_S.E._Tswana (HGDP) 22.86
5 Bantu_S.W._Herero (HGDP) 26.8
6 Mandenka (HGDP) 35.34
7 Yoruba (HGDP) 38.45
8 YRI30 (HGDP) 38.45
9 MKK30 (Dodecad) 79.55
10 Sandawe_He (Henn) 81.87
11 Algerian (Dodecad) 86.37
12 Yemenese (Behar) 86.5
13 Moroccans (Behar) 88.52
14 Egyptans (Behar) 89.66
15 Moroccan (Dodecad) 92.78
16 Uzbeks (Behar) 93.97
17 Jordanians (Behar) 94.29
18 O_Italian (Dodecad) 94.35
19 Turkmens (Yunusbayev) 94.36
20 Tajiks (Yunusbayev) 94.49

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 81.4% Bantu_S.E._Tswana (HGDP) + 18.6% German (Dodecad) @ 3.42
2 81.2% Bantu_S.E._Tswana (HGDP) + 18.8% Hungarians (Behar) @ 3.44
3 81.4% Bantu_S.E._Tswana (HGDP) + 18.6% Mixed_Germanic (Dodecad) @ 3.59
4 81.3% Bantu_S.E._Tswana (HGDP) + 18.7% French (Dodecad) @ 3.75
5 81.5% Bantu_S.E._Tswana (HGDP) + 18.5% Dutch (Dodecad) @ 3.75
6 81.4% Bantu_S.E._Tswana (HGDP) + 18.6% French (HGDP) @ 3.83
7 81.6% Bantu_S.E._Tswana (HGDP) + 18.4% Kent (1000Genomes) @ 3.97
8 81.6% Bantu_S.E._Tswana (HGDP) + 18.4% CEU30 (1000Genomes) @ 3.99
9 81.6% Bantu_S.E._Tswana (HGDP) + 18.4% English (Dodecad) @ 4.01
10 81% Bantu_S.E._Tswana (HGDP) + 19% Romanians (Behar) @ 4.14
11 81.7% Bantu_S.E._Tswana (HGDP) + 18.3% British_Isles (Dodecad) @ 4.15
12 81.7% Bantu_S.E._Tswana (HGDP) + 18.3% Cornwall (1000Genomes) @ 4.23
13 81.7% Bantu_S.E._Tswana (HGDP) + 18.3% British (Dodecad) @ 4.26
14 81.7% Bantu_S.E._Tswana (HGDP) + 18.3% Argyll (1000Genomes) @ 4.27
15 81.8% Bantu_S.E._Tswana (HGDP) + 18.2% Orkney (1000Genomes) @ 4.35
16 81.7% Bantu_S.E._Tswana (HGDP) + 18.3% Irish (Dodecad) @ 4.36
17 81.8% Bantu_S.E._Tswana (HGDP) + 18.2% Orcadian (HGDP) @ 4.37
18 81% Bantu_S.E._Tswana (HGDP) + 19% Bulgarian (Dodecad) @ 4.37
19 81.1% Bantu_S.E._Tswana (HGDP) + 18.9% Bulgarians (Yunusbayev) @ 4.38
20 81.9% Bantu_S.E._Tswana (HGDP) + 18.1% Norwegian (Dodecad) @ 4.5

Gedmatch.Com

My Autossomal Dodecad K12b 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

12 components mode.
Component threshold auto-set to 1.010%. Admix results below that value will not be considered.

Kit Number: F214911

Admix Results (sorted):

# Population Percent
1 Sub_Saharan 71.77
2 East_African 9.26
3 North_European 7.09
4 Atlantic_Med 5.62
5 Caucasus 2.04
6 Northwest_African 1.62
7 East_Asian 1.31
8 Siberian 1.28

——————————–

Least-squares method.

Using 1 population approximation:
1 ASW30 @ 14.420
2 Bantu_N.E. @ 17.371
3 LWK30 @ 18.269
4 Bantu_S.E._Tswana @ 18.707
5 Bantu_S.E._Pedi @ 18.842
6 Bantu_S.E._Zulu @ 20.115
7 Bantu_S.E._S.Sotho @ 20.444
8 Bantu_S.W._Herero @ 21.673
9 Bantu_S.W._Ovambo @ 24.015
10 Mandenka @ 28.775
223 iterations.

Using 2 populations approximation:
1 50% ASW30 +50% LWK30 @ 10.402
2 50% ASW30 +50% Bantu_N.E. @ 10.805
3 50% ASW30 +50% ASW30 @ 14.420
4 50% ASW30 +50% Bantu_S.E._Tswana @ 15.070
5 50% ASW30 +50% Bantu_S.E._Pedi @ 15.176
6 50% ASW30 +50% Bantu_S.E._Zulu @ 16.102
7 50% ASW30 +50% Bantu_S.E._S.Sotho @ 16.325
8 50% Bantu_S.E._Tswana +50% LWK30 @ 16.500
9 50% Bantu_S.E._Pedi +50% LWK30 @ 16.504
10 50% Bantu_N.E. +50% Bantu_S.E._Tswana @ 16.578
24976 iterations.

Using 3 populations approximation:
1 50% Bantu_S.E._Tswana +25% Hungarians +25% Yoruba @ 7.451
2 50% Bantu_S.E._Tswana +25% Hungarians +25% YRI30 @ 7.451
3 50% Bantu_S.W._Ovambo +25% Bantu_S.E._Pedi +25% Hungarians @ 7.451
4 50% Bantu_S.W._Ovambo +25% Bantu_S.E._Tswana +25% Hungarians @ 7.452
5 50% Bantu_S.E._Pedi +25% Hungarians +25% Yoruba @ 7.452
6 50% Bantu_S.E._Pedi +25% Hungarians +25% YRI30 @ 7.452
7 50% Yoruba +25% Hungarians +25% LWK30 @ 7.455
8 50% YRI30 +25% Hungarians +25% LWK30 @ 7.455
9 50% Bantu_S.W._Herero +25% Bantu_S.W._Ovambo +25% Hungarians @ 7.459
10 50% Bantu_S.W._Herero +25% Bantu_S.W._Herero +25% Hungarians @ 7.468
605458 iterations.

Using 4 populations approximation:
1 Bantu_S.E._Tswana + Bantu_S.E._Tswana + Hungarians + Yoruba @ 7.451
2 Bantu_S.E._Tswana + Bantu_S.E._Tswana + Hungarians + YRI30 @ 7.451
3 Bantu_S.E._Pedi + Bantu_S.W._Ovambo + Bantu_S.W._Ovambo + Hungarians @ 7.451
4 Bantu_S.E._Pedi + Bantu_S.E._Tswana + Hungarians + Yoruba @ 7.451
5 Bantu_S.E._Pedi + Bantu_S.E._Tswana + Hungarians + YRI30 @ 7.451
6 Bantu_S.E._Tswana + Bantu_S.W._Ovambo + Bantu_S.W._Ovambo + Hungarians @ 7.452
7 Bantu_S.E._Pedi + Bantu_S.E._Pedi + Hungarians + Yoruba @ 7.452
8 Bantu_S.E._Pedi + Bantu_S.E._Pedi + Hungarians + YRI30 @ 7.452
9 Bantu_S.E._S.Sotho + Bantu_S.W._Herero + Bantu_S.W._Ovambo + Hungarians @ 7.452
10 Hungarians + LWK30 + Yoruba + Yoruba @ 7.455
11 Hungarians + LWK30 + Yoruba + YRI30 @ 7.455
12 Hungarians + LWK30 + YRI30 + YRI30 @ 7.455
13 Bantu_S.E._Zulu + Bantu_S.W._Herero + Bantu_S.W._Ovambo + Hungarians @ 7.457
14 Bantu_S.W._Herero + Bantu_S.W._Herero + Bantu_S.W._Ovambo + Hungarians @ 7.459
15 Bantu_S.W._Herero + Bantu_S.W._Herero + Bantu_S.W._Herero + Hungarians @ 7.468
16 Bantu_S.E._Zulu + Bantu_S.W._Ovambo + Bantu_S.W._Ovambo + Hungarians @ 7.472
17 Bantu_S.E._S.Sotho + Bantu_S.E._S.Sotho + Bantu_S.W._Ovambo + Hungarians @ 7.479
18 Bantu_S.E._Tswana + Bantu_S.E._Zulu + Hungarians + Yoruba @ 7.480
19 Bantu_S.E._Tswana + Bantu_S.E._Zulu + Hungarians + YRI30 @ 7.480
20 Bantu_S.E._S.Sotho + Bantu_S.W._Ovambo + Bantu_S.W._Ovambo + Hungarians @ 7.483

2641111 iterations.

Done.

Elapsed time 2.0154 seconds.

Gedmatch.Com

My Autossomal Dodecad K12b 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. 223 populations found.
12 population clusters.

Kit Number: F214911

Admix Results:

# Population Percent
1 Gedrosia 0.95
2 Siberian 1.26
3 Northwest_African 1.59
4 Southeast_Asian 0.17
5 Atlantic_Med 5.53
6 North_European 6.97
7 South_Asian 0.21
8 East_African 9.10
9 Southwest_Asian 0.36
10 East_Asian 1.28
11 Caucasus 2.01
12 Sub_Saharan 70.55

Pct. Calc. Option 2

0 Unable to determine 0.01%
1 ASW30 58.39%
2 Mandenka 17.90%
3 Somali 6.22%
4 Sandawe_He 6.19%
5 Chuvashs 4.90%
6 Yoruba 2.17%
7 Nogais 1.85%
8 Andalucia 1.26%
9 Naga 1.11%
10 MKK30 0.00%

Total RMSD: 0.440808

Elapsed time 0.5645 seconds.

Publicado em My Autossomal Gedmatch Dodecad Project Admixture Oracle results | Marcado com | Deixe um comentário

My Autossomal Gedmatch Eurogenes Project Admixture Oracle results


My Autossomal EurogenesProject Admixture Oracle results

ANTONIO FLORENTINO

ANTONIO FLORENTINO

My Autossomal Gedmatch Eurogenes Project Admixture Oracle results

My Autossomal Gedmatch Eurogenes Project Admixture Oracle results

GEDmatch.Com Oracle

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.

My Autossomal Eurogenes K13 Oracle results:

K13 Oracle ref data revised 21 Nov 2013

Kit F214911

Admix Results (sorted):

# Population Percent
1 Sub-Saharan 71.29
2 West_Med 6.47
3 Northeast_African 6.35
4 Amerindian 4.12
5 North_Atlantic 4.06
6 Baltic 3.43
7 West_Asian 1.47
8 Red_Sea 1.21
9 East_Med 0.99
10 East_Asian 0.57
11 Oceanian 0.03
12 South_Asian 0.01

Single Population Sharing:

# Population (source) Distance
1 Bantu_S.E. 19.33
2 Biaka_Pygmy 19.93
3 Bantu_S.W. 20.08
4 Luhya 22.03
5 Mandenka 22.03
6 Bantu_N.E. 22.14
7 Yoruban 29.03
8 Mbuti_Pygmy 30.56
9 San 39.57
10 Sandawe 60.9
11 Sudanese 64.95
12 Maasai 69.58
13 Ethiopian_Anuak 70.76
14 Mozabite_Berber 74.81
15 Hadza 75.43
16 Algerian 76.68
17 Moroccan 78.62
18 Egyptian 83.92
19 Bedouin 87.7
20 Bulgarian 87.98

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 80.8% Mandenka + 19.2% North_Italian @ 6.06
2 80.6% Mandenka + 19.4% Romanian @ 6.13
3 81.3% Mandenka + 18.7% Southwest_French @ 6.15
4 80.7% Mandenka + 19.3% Spanish_Galicia @ 6.17
5 80.7% Mandenka + 19.3% Spanish_Extremadura @ 6.18
6 80.6% Mandenka + 19.4% Bulgarian @ 6.18
7 80.7% Mandenka + 19.3% Portuguese @ 6.22
8 81.1% Mandenka + 18.9% Spanish_Cantabria @ 6.25
9 81% Mandenka + 19% Spanish_Andalucia @ 6.3
10 81.1% Mandenka + 18.9% Spanish_Castilla_La_Mancha @ 6.33
11 80.7% Mandenka + 19.3% Serbian @ 6.34
12 80.9% Mandenka + 19.1% Spanish_Castilla_Y_Leon @ 6.36
13 80.9% Mandenka + 19.1% Spanish_Murcia @ 6.38
14 81% Mandenka + 19% Spanish_Valencia @ 6.38
15 81% Mandenka + 19% Spanish_Cataluna @ 6.41
16 80.8% Mandenka + 19.2% Tuscan @ 6.47
17 81.1% Mandenka + 18.9% French @ 6.57
18 81.4% Mandenka + 18.6% Spanish_Aragon @ 6.61
19 81% Mandenka + 19% Hungarian @ 6.66
20 81.1% Mandenka + 18.9% Austrian @ 6.77

Gedmatch.Com

My Autossomal Eurogenes K13 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

13 components mode.
Component threshold auto-set to 0.930%. Admix results below that value will not be considered.

Kit Number: F214911

Admix Results (sorted):

# Population Percent
1 Sub-Saharan 71.73
2 West_Med 6.51
3 Northeast_African 6.39
4 Amerindian 4.14
5 North_Atlantic 4.09
6 Baltic 3.45
7 West_Asian 1.48
8 Red_Sea 1.22
9 East_Med 1.00

——————————–

Least-squares method.

Using 1 population approximation:
1 Bantu_S.E. @ 17.650
2 Bantu_S.W. @ 18.129
3 Biaka_Pygmy @ 18.804
4 Mandenka @ 19.494
5 Luhya @ 21.025
6 Bantu_N.E. @ 21.181
7 Yoruban @ 25.508
8 Yoruban @ 25.508
9 Mbuti_Pygmy @ 28.949
10 San @ 37.093
179 iterations.

Using 2 populations approximation:
1 50% Bantu_N.E. +50% Mandenka @ 15.976
2 50% Luhya +50% Mandenka @ 16.275
3 50% Bantu_N.E. +50% Yoruban @ 16.816
4 50% Bantu_N.E. +50% Yoruban @ 16.816
5 50% Biaka_Pygmy +50% Mandenka @ 17.050
6 50% Luhya +50% Yoruban @ 17.234
7 50% Luhya +50% Yoruban @ 17.234
8 50% Bantu_N.E. +50% Bantu_S.W. @ 17.312
9 50% Bantu_S.W. +50% Luhya @ 17.514
10 50% Mbuti_Pygmy +50% Yoruban @ 17.624
16110 iterations.

Using 3 populations approximation:
1 50% Yoruban +25% Bantu_S.W. +25% Romanian @ 7.555
2 50% Yoruban +25% Bantu_S.W. +25% Romanian @ 7.555
3 50% Yoruban +25% Bantu_S.W. +25% Bulgarian @ 7.602
4 50% Yoruban +25% Bantu_S.W. +25% Bulgarian @ 7.602
5 50% Yoruban +25% Bantu_S.W. +25% North_Italian @ 7.619
6 50% Yoruban +25% Bantu_S.W. +25% North_Italian @ 7.619
7 50% Yoruban +25% Bantu_S.E. +25% Romanian @ 7.636
8 50% Yoruban +25% Bantu_S.E. +25% Romanian @ 7.636
9 50% Yoruban +25% Bantu_S.E. +25% Bulgarian @ 7.682
10 50% Yoruban +25% Bantu_S.E. +25% Bulgarian @ 7.682
502995 iterations.

Using 4 populations approximation:
1 Bantu_S.W. + Romanian + Yoruban + Yoruban @ 7.555
2 Bantu_S.W. + Romanian + Yoruban + Yoruban @ 7.555
3 Bantu_S.W. + Romanian + Yoruban + Yoruban @ 7.555
4 Bantu_S.W. + Bulgarian + Yoruban + Yoruban @ 7.602
5 Bantu_S.W. + Bulgarian + Yoruban + Yoruban @ 7.602
6 Bantu_S.W. + Bulgarian + Yoruban + Yoruban @ 7.602
7 Bantu_S.W. + North_Italian + Yoruban + Yoruban @ 7.619
8 Bantu_S.W. + North_Italian + Yoruban + Yoruban @ 7.619
9 Bantu_S.W. + North_Italian + Yoruban + Yoruban @ 7.619
10 Bantu_S.E. + Romanian + Yoruban + Yoruban @ 7.636
11 Bantu_S.E. + Romanian + Yoruban + Yoruban @ 7.636
12 Bantu_S.E. + Romanian + Yoruban + Yoruban @ 7.636
13 Bantu_S.E. + Bulgarian + Yoruban + Yoruban @ 7.682
14 Bantu_S.E. + Bulgarian + Yoruban + Yoruban @ 7.682
15 Bantu_S.E. + Bulgarian + Yoruban + Yoruban @ 7.682
16 Bantu_S.E. + North_Italian + Yoruban + Yoruban @ 7.692
17 Bantu_S.E. + North_Italian + Yoruban + Yoruban @ 7.692
18 Bantu_S.E. + North_Italian + Yoruban + Yoruban @ 7.692
19 Bantu_S.W. + Spanish_Galicia + Yoruban + Yoruban @ 7.805
20 Bantu_S.W. + Spanish_Galicia + Yoruban + Yoruban @ 7.805

2492859 iterations.

Done.

Elapsed time 1.6661 seconds.

Gedmatch.Com

My Autossomal Eurogenes K13 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. 179 populations found.
13 population clusters.

Kit Number: F214911

Admix Results:

# Population Percent
1 North_Atlantic 4.06
2 Baltic 3.43
3 West_Med 6.47
4 West_Asian 1.47
5 East_Med 0.99
6 Red_Sea 1.21
7 South_Asian 0.01
8 East_Asian 0.57
9 Siberian 0.00
10 Amerindian 4.12
11 Oceanian 0.03
12 Northeast_African 6.35
13 Sub-Saharan 71.29

Pct. Calc. Option 2

0 Unable to determine 0.01%
1 Mandenka 38.18%
2 Yoruban 33.67%
3 Romanian 7.64%
4 Luhya 5.93%
5 Mayan 4.77%
6 Sardinian 4.69%
7 French_Basque 3.73%
8 Sudanese 1.25%
9 Erzya 0.12%
10 Karitiana 0.01%

Total RMSD: 0.776208

Elapsed time 0.5765 seconds.

GEDmatch.Com Oracle

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.

My Autossomal Eurogenes EUtest V2 K15 Oracle results:

Kit F214911

Admix Results (sorted):

# Population Percent
1 Sub-Saharan 72.48
2 Northeast_African 5.76
3 West_Med 5.6
4 Atlantic 5.25
5 Amerindian 3.76
6 Eastern_Euro 3.63
7 Red_Sea 1.32
8 West_Asian 1.2
9 Baltic 0.7
10 Southeast_Asian 0.21
11 Oceanian 0.09

Single Population Sharing:

# Population (source) Distance
1 Biaka_Pygmy 19.49
2 Bantu_S.E. 20.21
3 Bantu_S.W. 21.09
4 Bantu_N.E. 21.39
5 Luhya 21.46
6 Mandenka 23
7 Mbuti_Pygmy 26.69
8 Yoruban 29.53
9 San 39.85
10 Sudanese 53.68
11 Ethiopian_Anuak 60.59
12 Sandawe 65.06
13 Maasai 70.95
14 Hadza 76.14
15 Mozabite_Berber 79.06
16 Algerian 80.71
17 Ethiopian_Gumuz 82.44
18 Moroccan 82.97
19 Egyptian 88.44
20 Bulgarian 91.27

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 80.8% Mandenka + 19.2% Southwest_French @ 6.18
2 80.6% Mandenka + 19.4% Spanish_Andalucia @ 6.26
3 80.7% Mandenka + 19.3% Spanish_Cantabria @ 6.3
4 80.8% Mandenka + 19.2% Spanish_Castilla_La_Mancha @ 6.32
5 80.7% Mandenka + 19.3% Spanish_Valencia @ 6.4
6 80.9% Mandenka + 19.1% Spanish_Aragon @ 6.41
7 80.5% Mandenka + 19.5% Spanish_Extremadura @ 6.47
8 80.7% Mandenka + 19.3% Spanish_Murcia @ 6.56
9 80.6% Mandenka + 19.4% Portuguese @ 6.6
10 80.7% Mandenka + 19.3% North_Italian @ 6.6
11 80.6% Mandenka + 19.4% Spanish_Castilla_Y_Leon @ 6.63
12 80.7% Mandenka + 19.3% Spanish_Cataluna @ 6.68
13 80.6% Mandenka + 19.4% Spanish_Galicia @ 6.73
14 81.4% Mandenka + 18.6% French_Basque @ 6.73
15 80.7% Mandenka + 19.3% Tuscan @ 6.99
16 80.6% Mandenka + 19.4% Bulgarian @ 7.05
17 80.6% Mandenka + 19.4% Serbian @ 7.09
18 80.6% Mandenka + 19.4% Romanian @ 7.12
19 81.7% Mandenka + 18.3% Sardinian @ 7.17
20 80.7% Mandenka + 19.3% Greek @ 7.21

Gedmatch.Com

My Autossomal Eurogenes EUtest V2 K15 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

15 components mode.
Component threshold auto-set to 0.810%. Admix results below that value will not be considered.

Kit Number: F214911

Admix Results (sorted):

# Population Percent
1 Sub-Saharan 73.21
2 Northeast_African 5.82
3 West_Med 5.66
4 Atlantic 5.30
5 Amerindian 3.80
6 Eastern_Euro 3.67
7 Red_Sea 1.33
8 West_Asian 1.21

——————————–

Least-squares method.

Using 1 population approximation:
1 Bantu_S.E. @ 17.676
2 Biaka_Pygmy @ 17.885
3 Bantu_S.W. @ 18.175
4 Mandenka @ 19.367
5 Luhya @ 20.365
6 Bantu_N.E. @ 20.368
7 Yoruban @ 24.687
8 Yoruban @ 24.687
9 Mbuti_Pygmy @ 25.339
10 San @ 37.169
165 iterations.

Using 2 populations approximation:
1 50% Bantu_N.E. +50% Mandenka @ 16.080
2 50% Luhya +50% Mandenka @ 16.406
3 50% Bantu_N.E. +50% Yoruban @ 16.964
4 50% Bantu_N.E. +50% Yoruban @ 16.964
5 50% Mandenka +50% Mbuti_Pygmy @ 16.966
6 50% Biaka_Pygmy +50% Mandenka @ 17.079
7 50% Bantu_N.E. +50% Bantu_S.W. @ 17.124
8 50% Mbuti_Pygmy +50% Yoruban @ 17.236
9 50% Mbuti_Pygmy +50% Yoruban @ 17.236
10 50% Bantu_S.W. +50% Luhya @ 17.372
13695 iterations.

Using 3 populations approximation:
1 50% Yoruban +25% Bantu_S.W. +25% Spanish_Andalucia @ 8.208
2 50% Yoruban +25% Bantu_S.W. +25% Spanish_Andalucia @ 8.208
3 50% Yoruban +25% Spanish_Andalucia +25% Yoruban @ 8.220
4 50% Yoruban +25% Spanish_Andalucia +25% Yoruban @ 8.220
5 50% Yoruban +25% Spanish_Andalucia +25% Yoruban @ 8.220
6 50% Yoruban +25% Spanish_Andalucia +25% Yoruban @ 8.220
7 50% Yoruban +25% Mandenka +25% Spanish_Andalucia @ 8.245
8 50% Yoruban +25% Mandenka +25% Spanish_Andalucia @ 8.245
9 50% Yoruban +25% Bantu_S.E. +25% Spanish_Andalucia @ 8.326
10 50% Yoruban +25% Bantu_S.E. +25% Spanish_Andalucia @ 8.326
423417 iterations.

Using 4 populations approximation:
1 Bantu_S.W. + Spanish_Andalucia + Yoruban + Yoruban @ 8.208
2 Bantu_S.W. + Spanish_Andalucia + Yoruban + Yoruban @ 8.208
3 Bantu_S.W. + Spanish_Andalucia + Yoruban + Yoruban @ 8.208
4 Spanish_Andalucia + Yoruban + Yoruban + Yoruban @ 8.220
5 Spanish_Andalucia + Yoruban + Yoruban + Yoruban @ 8.220
6 Spanish_Andalucia + Yoruban + Yoruban + Yoruban @ 8.220
7 Spanish_Andalucia + Yoruban + Yoruban + Yoruban @ 8.220
8 Mandenka + Spanish_Andalucia + Yoruban + Yoruban @ 8.245
9 Mandenka + Spanish_Andalucia + Yoruban + Yoruban @ 8.245
10 Mandenka + Spanish_Andalucia + Yoruban + Yoruban @ 8.245
11 Bantu_S.E. + Spanish_Andalucia + Yoruban + Yoruban @ 8.326
12 Bantu_S.E. + Spanish_Andalucia + Yoruban + Yoruban @ 8.326
13 Bantu_S.E. + Spanish_Andalucia + Yoruban + Yoruban @ 8.326
14 Bantu_S.W. + Spanish_Extremadura + Yoruban + Yoruban @ 8.347
15 Bantu_S.W. + Spanish_Extremadura + Yoruban + Yoruban @ 8.347
16 Bantu_S.W. + Spanish_Extremadura + Yoruban + Yoruban @ 8.347
17 Spanish_Extremadura + Yoruban + Yoruban + Yoruban @ 8.379
18 Spanish_Extremadura + Yoruban + Yoruban + Yoruban @ 8.379
19 Spanish_Extremadura + Yoruban + Yoruban + Yoruban @ 8.379
20 Spanish_Extremadura + Yoruban + Yoruban + Yoruban @ 8.379

1267272 iterations.

Done.

Elapsed time 1.1548 seconds.

Gedmatch.Com

My Autossomal Eurogenes EUtest V2 K15 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. 165 populations found.
15 population clusters.

Kit Number: F214911

Admix Results:

# Population Percent
1 North_Sea 0.00
2 Atlantic 5.25
3 Baltic 0.70
4 Eastern_Euro 3.63
5 West_Med 5.60
6 West_Asian 1.20
7 East_Med 0.00
8 Red_Sea 1.32
9 South_Asian 0.00
10 Southeast_Asian 0.21
11 Siberian 0.00
12 Amerindian 3.76
13 Oceanian 0.09
14 Northeast_African 5.76
15 Sub-Saharan 72.48

Pct. Calc. Option 2

0 Unable to determine 0.20%
1 Mandenka 40.26%
2 Yoruban 32.61%
3 Southwest_French 9.52%
4 Bantu_N.E. 5.84%
5 Sardinian 5.10%
6 Pima 4.83%
7 Chuvash 1.13%
8 Maasai 0.41%
9 French_Basque 0.11%
10 Mayan 0.00%

Total RMSD: 1.127317

Elapsed time 0.6469 seconds.

My Autossomal Eurogenes K9b Admixture Proportions
This utility uses the Eurogenes K9b model, created by Davidski (Polako). This model approximates the Geno 2.0 analysis. Questions and comments about this model
should be directed to him at his Project Blog.

Kit Number: F214911   Iteration: 1000   Delta-Q: 8.981201e-04   Elapsed Time: 91.21 seconds

Population
Southwest_Asian 1.98%
Native_American 3.65%
Northeast_Asian
Mediterranean 3.11%
North_European 14.20%
Southeast_Asian 0.82%
Oceanian
South_African 5.20%
Sub-Saharan_African 71.02%

 

Web site and contents ©Copyright 2011-2014 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions ‘calculator’ model remains the property of its developer.

My Autossomal Eurogenes K9 Admixture Proportions
This utility uses the Eurogenes K9 model, created by Davidski (Polako). Questions and comments about this model
should be directed to him at his Eurogenes blog. We appreciate him making this excellent tool available here.

A map showing the K9 populations is available HERE.

Population descriptions are available HERE.

Kit Number: F214911   Iteration: 1000   Delta-Q: 6.043257e-01   Elapsed Time: 119.32 seconds

Population
South Asian 0.33%
Caucasus 2.20%
Southwest Asian 0.68%
North Amerindian + Arctic 3.30%
Siberian
Mediterranean 7.23%
East Asian 0.06%
West African 78.17%
North European 8.04%

 

Web site and contents ©Copyright 2011-2014 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions ‘calculator’ model remains the property of its developer.

My Autossomal Eurogenes K10 Admixture Proportions
This utility uses the Eurogenes K10 model, created by Davidski (Polako). Questions and comments about this model
should be directed to him at his Eurogenes blog. We appreciate him making this excellent tool available here.

A map showing the K10 populations is available HERE.

Population descriptions are available HERE.

Kit Number: F214911   Iteration: 1000   Delta-Q: 1.592713e-01   Elapsed Time: 147.06 seconds

Population
South Asian 0.35%
Caucasus 2.16%
Southwest Asian 0.65%
North Amerindian + Arctic 3.30%
Siberian
Mediterranean 6.54%
East Asian
West African 78.16%
East European 4.93%
North Atlantic 3.90%

 

Web site and contents ©Copyright 2011-2014 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions ‘calculator’ model remains the property of its developer.

My Autossomal Eurogenes K11 Admixture Proportions
This utility uses the Davidski/Polako Eurogenes K11 model. Questions and comments about this model
should be directed to him at his Eurogenes blog. We appreciate him making this excellent tool available here.

A map showing the K11 populations is available HERE.

Population descriptions are available HERE.

Kit Number: F214911   Iteration: 1000   Delta-Q: 1.507533e-04   Elapsed Time: 108.81 seconds

Population
South Asian 0.14%
Caucasus 1.83%
Southwest Asian 0.62%
North Amerindian + Arctic 3.18%
Siberian
Mediterranean 6.45%
East Asian
West African 78.13%
Volga-Ural 4.15%
South Baltic 1.84%
North Atlantic 3.66%

 

Web site and contents ©Copyright 2011-2014 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions ‘calculator’ model remains the property of its developer.

My Autossomal Eurogenes K12 Admixture Proportions
This utility uses the Eurogenes K12 model, created by Davidski (Polako). Questions and comments about this model
should be directed to him at his Eurogenes blog. We appreciate him making this excellent tool available here.

A map showing the K12 populations is available HERE.

Population descriptions are available HERE.

Kit Number: F214911   Iteration: 1000   Delta-Q: 9.071796e-02   Elapsed Time: 167.12 seconds

Population
South Asian 0.14%
Caucasus 1.87%
Southwest Asian 0.58%
North Amerindian + Arctic 3.18%
Siberian
Mediterranean 5.65%
East Asian
West African 78.12%
Volga-Ural 4.04%
South Baltic 1.72%
Western European 4.68%
North Sea

 

Web site and contents ©Copyright 2011-2014 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions ‘calculator’ model remains the property of its developer.

My Autossomal Eurogenes K12b Admixture Proportions
This utility uses the revised Eurogenes K12b model, created by Davidski (Polako). The old K12b model has been removed. Questions and comments about this model
should be directed to him at his Eurogenes blog. We appreciate him making this excellent tool available here.

A map showing the K12b populations is available HERE.

Population descriptions are available HERE.

Kit Number: F214911   Iteration: 425   Delta-Q: 9.847863e-07   Elapsed Time: 56.63 seconds

Population
Western European 4.59%
Siberian 1.81%
East African 8.01%
West Central Asian 0.69%
South Asian 1.00%
West African 69.91%
Caucasus 0.71%
Finnish 0.49%
Mediterranean 5.28%
Southwest Asian 0.82%
North European 5.46%
East Asian 1.22%

 

Web site and contents ©Copyright 2011-2014 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions ‘calculator’ model remains the property of its developer.

My Autossomal Eurogenes K36 Admixture Proportions
This utility uses the Eurogenes K36 model, created by Davidski (Polako). Questions and comments about this model
should be directed to him at his Eurogenes Genetic Ancestry Project blog.

Kit Number: F214911   Iteration: 1000   Delta-Q: 8.858657e-01   Elapsed Time: 321.30 seconds

Population
Amerindian 3.34%
Arabian
Armenian
Basque 1.14%
Central_African 4.01%
Central_Euro 1.19%
East_African 5.22%
East_Asian
East_Balkan
East_Central_Asian
East_Central_Euro 0.14%
East_Med
Eastern_Euro 1.71%
Fennoscandian 0.45%
French 0.67%
Iberian 0.23%
Indo-Chinese
Italian 5.59%
Malayan
Near_Eastern
North_African
North_Atlantic 0.78%
North_Caucasian
North_Sea
Northeast_African
Oceanian
Omotic
Pygmy 6.83%
Siberian
South_Asian 0.21%
South_Central_Asian
South_Chinese
Volga-Ural 1.18%
West_African 63.58%
West_Caucasian 1.26%
West_Med 2.48%

 

Web site and contents ©Copyright 2011-2014 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions ‘calculator’ model remains the property of its developer.

My Autossomal Eurogenes Hunter_Gatherer vs. Farmer Admixture Proportions
This utility uses the Hunter_Gatherer vs. Farmer model, created by Davidski (Polako). Questions and comments about this model
should be directed to him at his Eurogenes blog. We appreciate him making this excellent tool available here.

A map showing the HGvF populations is available HERE.

Population descriptions are available HERE.

Kit Number: F214911   Iteration: 1000   Delta-Q: 1.697309e-02   Elapsed Time: 151.60 seconds

Population
Anatolian Farmer 1.50%
Baltic Hunter Gatherer 7.13%
Middle Eastern Herder 0.91%
East Asian Farmer 0.25%
South American Hunter Gatherer 3.34%
South Asian Hunter Gatherer 0.62%
North Eurasian Hunter Gatherer
East African Pastoralist 7.17%
Oceanian Hunter Gatherer 0.12%
Mediterranean Farmer 7.34%
Pygmy Hunter Gatherer 6.50%
Bantu Farmer 65.12%

 

Web site and contents ©Copyright 2011-2014 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions ‘calculator’ model remains the property of its developer.

GEDmatch.Com Oracle

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.

My Autossomal Jtest Oracle results:

Jtest Oracle population reference data revised 06 Nov 2012.

Kit F214911

Admix Results (sorted):

# Population Percent
1 WEST_AFRICAN 61.95
2 EAST_AFRICAN 15.86
3 WEST_MED 5.1
4 EAST_EURO 5.02
5 ATLANTIC 2.42
6 MIDDLE_EASTERN 2.32
7 ASHKENAZI 1.69
8 SOUTH_BALTIC 1.67
9 SIBERIAN 1.26
10 SOUTH_ASIAN 1.13
11 EAST_ASIAN 0.96
12 NORTH-CENTRAL_EURO 0.6

Single Population Sharing:

# Population (source) Distance
1 Luhya 20.41
2 Yoruba 24.81
3 Maasai 65.17
4 Algerian 79.27
5 Mozabite_Berber 80.1
6 Moroccan 83.24
7 Somali 88.58
8 Ethiopian 88.94
9 PT 91.08
10 RO 91.36
11 Serbian 91.49
12 HU 91.83
13 South_Italian_&_Sicilian 92
14 North_Italian 92.14
15 ES 92.16
16 AT 92.16
17 Tuscan 92.49
18 AJ 92.94
19 FR 92.95
20 GR 93

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 79% Yoruba + 21% RO @ 5.59
2 79.1% Yoruba + 20.9% HU @ 5.64
3 79.1% Yoruba + 20.9% Serbian @ 5.72
4 79.2% Yoruba + 20.8% AT @ 5.93
5 79.1% Yoruba + 20.9% PT @ 5.99
6 79.3% Yoruba + 20.7% ES @ 6.04
7 79.5% Yoruba + 20.5% East_Russian @ 6.07
8 79.3% Yoruba + 20.7% North_Italian @ 6.07
9 79.4% Yoruba + 20.6% FR @ 6.24
10 79.7% Yoruba + 20.3% North_Russian @ 6.4
11 79.7% Yoruba + 20.3% Erzya @ 6.42
12 79.7% Yoruba + 20.3% Udmurt @ 6.44
13 79.6% Yoruba + 20.4% Ukrainian-Russian @ 6.45
14 79.6% Yoruba + 20.4% West_Russian @ 6.48
15 79.7% Yoruba + 20.3% UA @ 6.62
16 79.4% Yoruba + 20.6% Tuscan @ 6.68
17 79.7% Yoruba + 20.3% PL @ 6.72
18 79.8% Yoruba + 20.2% South_Finnish @ 6.8
19 79.6% Yoruba + 20.4% West_&_Central_German @ 6.81
20 79.8% Yoruba + 20.2% Komi @ 6.82

Gedmatch.Com

My Autossomal Jtest 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

14 components mode.
Component threshold auto-set to 0.870%. Admix results below that value will not be considered.

Kit Number: F214911

Admix Results (sorted):

# Population Percent
1 WEST_AFRICAN 62.33
2 EAST_AFRICAN 15.96
3 WEST_MED 5.13
4 EAST_EURO 5.05
5 ATLANTIC 2.44
6 MIDDLE_EASTERN 2.34
7 ASHKENAZI 1.70
8 SOUTH_BALTIC 1.68
9 SIBERIAN 1.27
10 SOUTH_ASIAN 1.14
11 EAST_ASIAN 0.96

——————————–

Least-squares method.

Using 1 population approximation:
1 Yoruba @ 16.949
2 Luhya @ 17.134
3 Maasai @ 52.222
4 Algerian @ 64.456
5 Mozabite_Berber @ 66.431
6 Moroccan @ 66.760
7 RO @ 71.543
8 Serbian @ 71.783
9 HU @ 72.239
10 PT @ 72.308
78 iterations.

Using 2 populations approximation:
1 50% Luhya +50% Yoruba @ 15.440
2 50% Yoruba +50% Yoruba @ 16.949
3 50% Luhya +50% Luhya @ 17.134
4 50% Maasai +50% Yoruba @ 24.560
5 50% Algerian +50% Yoruba @ 25.807
6 50% Moroccan +50% Yoruba @ 26.487
7 50% Mozabite_Berber +50% Yoruba @ 26.779
8 50% RO +50% Yoruba @ 28.463
9 50% Serbian +50% Yoruba @ 28.636
10 50% HU +50% Yoruba @ 28.797
3081 iterations.

Using 3 populations approximation:
1 50% Yoruba +25% RO +25% Yoruba @ 8.691
2 50% Yoruba +25% Moroccan +25% Yoruba @ 8.762
3 50% Yoruba +25% HU +25% Yoruba @ 8.796
4 50% Yoruba +25% Serbian +25% Yoruba @ 8.869
5 50% Yoruba +25% AT +25% Yoruba @ 9.206
6 50% Yoruba +25% PT +25% Yoruba @ 9.210
7 50% Yoruba +25% Algerian +25% Yoruba @ 9.377
8 50% Yoruba +25% North_Italian +25% Yoruba @ 9.402
9 50% Yoruba +25% ES +25% Yoruba @ 9.405
10 50% Yoruba +25% East_Russian +25% Yoruba @ 9.458
204199 iterations.

Using 4 populations approximation:
1 RO + Yoruba + Yoruba + Yoruba @ 8.691
2 Moroccan + Yoruba + Yoruba + Yoruba @ 8.762
3 HU + Yoruba + Yoruba + Yoruba @ 8.796
4 Serbian + Yoruba + Yoruba + Yoruba @ 8.869
5 AT + Yoruba + Yoruba + Yoruba @ 9.206
6 PT + Yoruba + Yoruba + Yoruba @ 9.210
7 Algerian + Yoruba + Yoruba + Yoruba @ 9.377
8 North_Italian + Yoruba + Yoruba + Yoruba @ 9.402
9 ES + Yoruba + Yoruba + Yoruba @ 9.405
10 East_Russian + Yoruba + Yoruba + Yoruba @ 9.458
11 Udmurt + Yoruba + Yoruba + Yoruba @ 9.646
12 Mozabite_Berber + Yoruba + Yoruba + Yoruba @ 9.691
13 FR + Yoruba + Yoruba + Yoruba @ 9.744
14 Ukrainian-Russian + Yoruba + Yoruba + Yoruba @ 9.774
15 West_Russian + Yoruba + Yoruba + Yoruba @ 9.824
16 Erzya + Yoruba + Yoruba + Yoruba @ 9.829
17 North_Russian + Yoruba + Yoruba + Yoruba @ 9.896
18 UA + Yoruba + Yoruba + Yoruba @ 9.973
19 Komi + Yoruba + Yoruba + Yoruba @ 10.069
20 PL + Yoruba + Yoruba + Yoruba @ 10.100

1000985 iterations.

Done.

Elapsed time 0.6970 seconds.

Gedmatch.Com

My Autossomal Jtest 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. 78 populations found.
14 population clusters.

Kit Number: F214911

Admix Results:

# Population Percent
1 SOUTH_BALTIC 1.67
2 EAST_EURO 5.02
3 NORTH-CENTRAL_EURO 0.60
4 ATLANTIC 2.42
5 WEST_MED 5.10
6 ASHKENAZI 1.69
7 EAST_MED 0.00
8 WEST_ASIAN 0.00
9 MIDDLE_EASTERN 2.32
10 SOUTH_ASIAN 1.13
11 EAST_AFRICAN 15.86
12 EAST_ASIAN 0.96
13 SIBERIAN 1.26
14 WEST_AFRICAN 61.95

Pct. Calc. Option 2

1 Yoruba 69.89%
2 RO 17.45%
3 Luhya 6.68%
4 Mozabite_Berber 3.74%
5 Chukchi 1.11%
6 Selkup 1.11%
7 Maasai 0.01%
8 Koryak 0.00%
9 Moroccan 0.00%
10 Sardinian 0.00%

Total RMSD: 1.722152

Elapsed time 0.8293 seconds.,

GEDmatch.Com Oracle

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.

My Autossomal EUtest Oracle results:

EUtest Oracle population reference data revised 06 Nov 2012.

Kit F214911

Admix Results (sorted):

# Population Percent
1 WEST_AFRICAN 61.91
2 EAST_AFRICAN 15.91
3 WEST_MED 5.4
4 EAST_EURO 5.16
5 MIDDLE_EASTERN 2.88
6 ATLANTIC 2.75
7 SOUTH_BALTIC 1.74
8 SOUTH_ASIAN 1.24
9 SIBERIAN 1.24
10 EAST_ASIAN 0.97
11 NORTH-CENTRAL_EURO 0.8

Single Population Sharing:

# Population (source) Distance
1 Luhya 20.21
2 Yoruba 24.6
3 Maasai 64.1
4 Algerian 78.75
5 Mozabite_Berber 78.9
6 Moroccan 82.71
7 Somali 87.23
8 Ethiopian 87.67
9 PT 90.07
10 RO 90.36
11 Serbian 90.38
12 HU 90.69
13 AJ 90.69
14 AT 91.02
15 ES 91.14
16 North_Italian 91.15
17 South_Italian_&_Sicilian 91.53
18 Tuscan 91.67
19 FR 91.86
20 West_&_Central_German 92.15

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 79.1% Yoruba + 20.9% HU @ 5.8
2 79.1% Yoruba + 20.9% RO @ 5.88
3 79.1% Yoruba + 20.9% Serbian @ 5.93
4 79% Yoruba + 21% PT @ 6.06
5 79.2% Yoruba + 20.8% AT @ 6.07
6 79.2% Yoruba + 20.8% ES @ 6.1
7 79.5% Yoruba + 20.5% East_Russian @ 6.18
8 79.3% Yoruba + 20.7% North_Italian @ 6.24
9 79.4% Yoruba + 20.6% FR @ 6.3
10 79.7% Yoruba + 20.3% North_Russian @ 6.49
11 79.6% Yoruba + 20.4% Erzya @ 6.55
12 79.6% Yoruba + 20.4% Udmurt @ 6.55
13 79.6% Yoruba + 20.4% Ukrainian-Russian @ 6.58
14 79.6% Yoruba + 20.4% West_Russian @ 6.6
15 79.6% Yoruba + 20.4% UA @ 6.72
16 79.7% Yoruba + 20.3% South_Finnish @ 6.82
17 79.6% Yoruba + 20.4% PL @ 6.83
18 79.6% Yoruba + 20.4% West_&_Central_German @ 6.86
19 79.7% Yoruba + 20.3% East_Finnish @ 6.88
20 79.6% Yoruba + 20.4% NL @ 6.89

Gedmatch.Com

My Autossomal EUtest 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

13 components mode.
Component threshold auto-set to 0.930%. Admix results below that value will not be considered.

Kit Number: F214911

Admix Results (sorted):

# Population Percent
1 WEST_AFRICAN 62.41
2 EAST_AFRICAN 16.04
3 WEST_MED 5.45
4 EAST_EURO 5.20
5 MIDDLE_EASTERN 2.91
6 ATLANTIC 2.77
7 SOUTH_BALTIC 1.75
8 SOUTH_ASIAN 1.25
9 SIBERIAN 1.25
10 EAST_ASIAN 0.97

——————————–

Least-squares method.

Using 1 population approximation:
1 Luhya @ 17.185
2 Yoruba @ 17.684
3 Maasai @ 52.083
4 Algerian @ 65.385
5 Mozabite_Berber @ 66.586
6 Moroccan @ 67.769
7 RO @ 72.211
8 Serbian @ 72.271
9 HU @ 72.648
10 Somali @ 72.690
78 iterations.

Using 2 populations approximation:
1 50% Luhya +50% Yoruba @ 15.790
2 50% Luhya +50% Luhya @ 17.185
3 50% Yoruba +50% Yoruba @ 17.684
4 50% Maasai +50% Yoruba @ 24.397
5 50% Algerian +50% Yoruba @ 26.009
6 50% Mozabite_Berber +50% Yoruba @ 26.552
7 50% Moroccan +50% Yoruba @ 26.723
8 50% RO +50% Yoruba @ 28.565
9 50% Serbian +50% Yoruba @ 28.630
10 50% HU +50% Yoruba @ 28.736
3081 iterations.

Using 3 populations approximation:
1 50% Yoruba +25% HU +25% Yoruba @ 8.769
2 50% Yoruba +25% RO +25% Yoruba @ 8.799
3 50% Yoruba +25% Moroccan +25% Yoruba @ 8.875
4 50% Yoruba +25% Serbian +25% Yoruba @ 8.895
5 50% Yoruba +25% PT +25% Yoruba @ 9.161
6 50% Yoruba +25% AT +25% Yoruba @ 9.187
7 50% Yoruba +25% ES +25% Yoruba @ 9.328
8 50% Yoruba +25% East_Russian +25% Yoruba @ 9.346
9 50% Yoruba +25% North_Italian +25% Yoruba @ 9.418
10 50% Yoruba +25% Algerian +25% Yoruba @ 9.498
204075 iterations.

Using 4 populations approximation:
1 HU + Yoruba + Yoruba + Yoruba @ 8.769
2 RO + Yoruba + Yoruba + Yoruba @ 8.799
3 Moroccan + Yoruba + Yoruba + Yoruba @ 8.875
4 Serbian + Yoruba + Yoruba + Yoruba @ 8.895
5 PT + Yoruba + Yoruba + Yoruba @ 9.161
6 AT + Yoruba + Yoruba + Yoruba @ 9.187
7 ES + Yoruba + Yoruba + Yoruba @ 9.328
8 East_Russian + Yoruba + Yoruba + Yoruba @ 9.346
9 North_Italian + Yoruba + Yoruba + Yoruba @ 9.418
10 Algerian + Yoruba + Yoruba + Yoruba @ 9.498
11 Udmurt + Yoruba + Yoruba + Yoruba @ 9.500
12 Mozabite_Berber + Yoruba + Yoruba + Yoruba @ 9.583
13 FR + Yoruba + Yoruba + Yoruba @ 9.670
14 Ukrainian-Russian + Yoruba + Yoruba + Yoruba @ 9.719
15 Erzya + Yoruba + Yoruba + Yoruba @ 9.724
16 West_Russian + Yoruba + Yoruba + Yoruba @ 9.742
17 North_Russian + Yoruba + Yoruba + Yoruba @ 9.754
18 UA + Yoruba + Yoruba + Yoruba @ 9.888
19 Komi + Yoruba + Yoruba + Yoruba @ 9.953
20 PL + Yoruba + Yoruba + Yoruba @ 10.032

983046 iterations.

Done.

Elapsed time 0.6015 seconds.

Gedmatch.Com

My Autossomal EUtest 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. 78 populations found.
13 population clusters.

Kit Number: F214911

Admix Results:

# Population Percent
1 SOUTH_BALTIC 1.74
2 EAST_EURO 5.16
3 NORTH-CENTRAL_EURO 0.80
4 ATLANTIC 2.75
5 WEST_MED 5.40
6 EAST_MED 0.00
7 WEST_ASIAN 0.00
8 MIDDLE_EASTERN 2.88
9 SOUTH_ASIAN 1.24
10 EAST_AFRICAN 15.91
11 EAST_ASIAN 0.97
12 SIBERIAN 1.24
13 WEST_AFRICAN 61.91

Pct. Calc. Option 2

1 Yoruba 69.09%
2 HU 17.54%
3 Luhya 6.96%
4 Mozabite_Berber 4.42%
5 Selkup 1.11%
6 Sardinian 0.67%
7 Chukchi 0.11%
8 Moroccan 0.11%
9 Maasai 0.00%
10 Bangladeshi 0.00%

Total RMSD: 1.747024

Elapsed time 0.5665 seconds.

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