Effective selection of informative SNPs and classification on the HapMap genotype data

Background: Since the single nucleotide polymorphisms (SNPs) are genetic variations which determine the difference between any two unrelated individuals, the SNPs can be used to identify the correct source population of an individual. For efficient population identification with the...

Full description

Saved in:
Bibliographic Details
Main Authors: Zhou, Nina., Wang, Lipo.
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2012
Subjects:
Online Access:https://hdl.handle.net/10356/94619
http://hdl.handle.net/10220/8131
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-94619
record_format dspace
spelling sg-ntu-dr.10356-946192022-02-16T16:28:23Z Effective selection of informative SNPs and classification on the HapMap genotype data Zhou, Nina. Wang, Lipo. School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Background: Since the single nucleotide polymorphisms (SNPs) are genetic variations which determine the difference between any two unrelated individuals, the SNPs can be used to identify the correct source population of an individual. For efficient population identification with the HapMap genotype data, as few informative SNPs as possible are required from the original 4 million SNPs. Recently, Park et al. (2006) adopted the nearest shrunken centroid method to classify the three populations, i.e., Utah residents with ancestry from Northern and Western Europe (CEU), Yoruba in Ibadan, Nigeria in West Africa (YRI), and Han Chinese in Beijing together with Japanese in Tokyo (CHB+JPT), from which 100,736 SNPs were obtained and the top 82 SNPs could completely classify the three populations. Published version 2012-05-23T02:57:30Z 2019-12-06T18:59:16Z 2012-05-23T02:57:30Z 2019-12-06T18:59:16Z 2007 2007 Journal Article Zhou, N., & Wang, L. (2007). Effective selection of informative SNPs and classification on the HapMap genotype data. BMC Bioinformatics, 8. https://hdl.handle.net/10356/94619 http://hdl.handle.net/10220/8131 10.1186/1471-2105-8-484 18093342 en BMC bioinformatics © 2007 The Authors; BioMed Central. This paper was published in BMC Bioinformatics and is made available as an electronic reprint (preprint) with permission of BioMed Central. The paper can be found at the following official URL: http://dx.doi.org/10.1186/1471-2105-8-484 .  One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. 9 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Zhou, Nina.
Wang, Lipo.
Effective selection of informative SNPs and classification on the HapMap genotype data
description Background: Since the single nucleotide polymorphisms (SNPs) are genetic variations which determine the difference between any two unrelated individuals, the SNPs can be used to identify the correct source population of an individual. For efficient population identification with the HapMap genotype data, as few informative SNPs as possible are required from the original 4 million SNPs. Recently, Park et al. (2006) adopted the nearest shrunken centroid method to classify the three populations, i.e., Utah residents with ancestry from Northern and Western Europe (CEU), Yoruba in Ibadan, Nigeria in West Africa (YRI), and Han Chinese in Beijing together with Japanese in Tokyo (CHB+JPT), from which 100,736 SNPs were obtained and the top 82 SNPs could completely classify the three populations.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Zhou, Nina.
Wang, Lipo.
format Article
author Zhou, Nina.
Wang, Lipo.
author_sort Zhou, Nina.
title Effective selection of informative SNPs and classification on the HapMap genotype data
title_short Effective selection of informative SNPs and classification on the HapMap genotype data
title_full Effective selection of informative SNPs and classification on the HapMap genotype data
title_fullStr Effective selection of informative SNPs and classification on the HapMap genotype data
title_full_unstemmed Effective selection of informative SNPs and classification on the HapMap genotype data
title_sort effective selection of informative snps and classification on the hapmap genotype data
publishDate 2012
url https://hdl.handle.net/10356/94619
http://hdl.handle.net/10220/8131
_version_ 1725985756008153088