↓ Skip to main content

PLOS

Identification of Close Relatives in the HUGO Pan-Asian SNP Database

Overview of attention for article published in PLOS ONE, December 2011
Altmetric Badge

Mentioned by

blogs
1 blog
wikipedia
1 Wikipedia page

Readers on

mendeley
50 Mendeley
citeulike
1 CiteULike
Title
Identification of Close Relatives in the HUGO Pan-Asian SNP Database
Published in
PLOS ONE, December 2011
DOI 10.1371/journal.pone.0029502
Pubmed ID
Authors

Xiong Yang, Shuhua Xu

Abstract

The HUGO Pan-Asian SNP Consortium has recently released a genome-wide dataset, which consists of 1,719 DNA samples collected from 71 Asian populations. For studies of human population genetics such as genetic structure and migration history, this provided the most comprehensive large-scale survey of genetic variation to date in East and Southeast Asia. However, although considered in the analysis, close relatives were not clearly reported in the original paper. Here we performed a systematic analysis of genetic relationships among individuals from the Pan-Asian SNP (PASNP) database and identified 3 pairs of monozygotic twins or duplicate samples, 100 pairs of first-degree and 161 second-degree of relationships. Three standardized subsets with different levels of unrelated individuals were suggested here for future applications of the samples in most types of population-genetics studies (denoted by PASNP1716, PASNP1640 and PASNP1583 respectively) based on the relationships inferred in this study. In addition, we provided gender information for PASNP samples, which were not included in the original dataset, based on analysis of X chromosome data.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 4%
Portugal 1 2%
Unknown 47 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 20%
Researcher 9 18%
Student > Master 6 12%
Professor 4 8%
Other 3 6%
Other 12 24%
Unknown 6 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 40%
Biochemistry, Genetics and Molecular Biology 10 20%
Medicine and Dentistry 3 6%
Unspecified 2 4%
Business, Management and Accounting 1 2%
Other 9 18%
Unknown 5 10%