How Many SNPs Should Be Used for the Human Phylogeny of Highly Related Ethnicities? A Case of Pan Asian 63 Ethnicities
In planning a model-based phylogenic study for highly related ethnic data, the SNP marker number is an important factor to determine for relationship inferences. Genotype frequency data, utilizing a sub sampling method,from 63 Pan Asian ethnic groups was used for determining the minimum SNP number r...
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Published in | Genomics & informatics Vol. 9; no. 4; pp. 181 - 188 |
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Main Authors | , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
한국유전체학회
31.12.2011
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Subjects | |
Online Access | Get full text |
ISSN | 1598-866X 2234-0742 |
DOI | 10.5808/GI.2011.9.4.181 |
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Abstract | In planning a model-based phylogenic study for highly related ethnic data, the SNP marker number is an important factor to determine for relationship inferences.
Genotype frequency data, utilizing a sub sampling method,from 63 Pan Asian ethnic groups was used for determining the minimum SNP number required to establish such relationships. Bootstrap random sub-samplings were done from 5.6K PASNPi SNP data. DA distance was calculated and neighbour-joining trees were drawn with every re-sampling data set. Consensus trees were made with the same 100 sub-samples and bootstrap proportions were calculated. The tree consistency to the one obtained from the whole marker set, improved with increasing marker numbers. The bootstrap proportions became reliable when more than 7,000 SNPs were used at a time. Within highly related ethnic groups, the minimum SNPs number for a robust neighbor-joining tree inference was about 7,000 for a 95% bootstrap support. KCI Citation Count: 0 |
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AbstractList | In planning a model-based phylogenic study for highly related ethnic data, the SNP marker number is an important factor to determine for relationship inferences.
Genotype frequency data, utilizing a sub sampling method,from 63 Pan Asian ethnic groups was used for determining the minimum SNP number required to establish such relationships. Bootstrap random sub-samplings were done from 5.6K PASNPi SNP data. DA distance was calculated and neighbour-joining trees were drawn with every re-sampling data set. Consensus trees were made with the same 100 sub-samples and bootstrap proportions were calculated. The tree consistency to the one obtained from the whole marker set, improved with increasing marker numbers. The bootstrap proportions became reliable when more than 7,000 SNPs were used at a time. Within highly related ethnic groups, the minimum SNPs number for a robust neighbor-joining tree inference was about 7,000 for a 95% bootstrap support. KCI Citation Count: 0 |
Author | Kim, Sang-Soo Kim, Chul-Hong Ghang, Ho-Young Youn, Chan-Hyun Bhak, Jong The HUGO Pan-Asian SNP Consortium, The HUGO Pan-Asian SNP Consortium Han, Young-Joo Kim, Tae-Hyung Lee, Sung-Hoon Yoo, Hyang-Sook Jeong, Sang-Jin Al-Mulla, Fahd |
Author_xml | – sequence: 1 givenname: Ho-Young surname: Ghang fullname: Ghang, Ho-Young – sequence: 2 givenname: Young-Joo surname: Han fullname: Han, Young-Joo – sequence: 3 givenname: Sang-Jin surname: Jeong fullname: Jeong, Sang-Jin – sequence: 4 givenname: Jong surname: Bhak fullname: Bhak, Jong – sequence: 5 givenname: Sung-Hoon surname: Lee fullname: Lee, Sung-Hoon – sequence: 6 givenname: Tae-Hyung surname: Kim fullname: Kim, Tae-Hyung – sequence: 7 givenname: Chul-Hong surname: Kim fullname: Kim, Chul-Hong – sequence: 8 givenname: Sang-Soo surname: Kim fullname: Kim, Sang-Soo – sequence: 9 givenname: Fahd surname: Al-Mulla fullname: Al-Mulla, Fahd – sequence: 10 givenname: Chan-Hyun surname: Youn fullname: Youn, Chan-Hyun – sequence: 11 givenname: Hyang-Sook surname: Yoo fullname: Yoo, Hyang-Sook – sequence: 12 givenname: The HUGO Pan-Asian SNP Consortium surname: The HUGO Pan-Asian SNP Consortium fullname: The HUGO Pan-Asian SNP Consortium, The HUGO Pan-Asian SNP Consortium |
BackLink | https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART001622902$$DAccess content in National Research Foundation of Korea (NRF) |
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