A new measure of population structure using multiple single nucleotide polymorphisms and its relationship with FST.

Hdl Handle:
http://hdl.handle.net/10675.2/90
Title:
A new measure of population structure using multiple single nucleotide polymorphisms and its relationship with FST.
Authors:
Xu, Hongyan; Sarkar, Bayazid; George, Varghese
Abstract:
BACKGROUND: Large-scale genome-wide association studies are promising for unraveling the genetic basis of complex diseases. Population structure is a potential problem, the effects of which on genetic association studies are controversial. The first step to systematically quantify the effects of population structure is to choose an appropriate measure of population structure for human data. The commonly used measure is Wright's FST. For a set of subpopulations it is generally assumed to be one value of FST. However, the estimates could be different for distinct loci. Since population structure is a concept at the population level, a measure of population structure that utilized the information across loci would be desirable. FINDINGS: In this study we propose an adjusted C parameter according to the sample size from each sub-population. The new measure C is based on the c parameter proposed for SNP data, which was assumed to be subpopulation-specific and common for all loci. In this study, we performed extensive simulations of samples with varying levels of population structure to investigate the properties and relationships of both measures. It is found that the two measures generally agree well. CONCLUSION: The new measure simultaneously uses the marker information across the genome. It has the advantage of easy interpretation as one measure of population structure and yet can also assess population differentiation.
Citation:
BMC Res Notes. 2009 Feb 6; 2:21
Issue Date:
16-Mar-2009
URI:
http://hdl.handle.net/10675.2/90
DOI:
10.1186/1756-0500-2-21
PubMed ID:
19284702
PubMed Central ID:
PMC2652468
Type:
Journal Article
ISSN:
1756-0500
Appears in Collections:
Department of Biostatistics and Epidemiology: Faculty Research and Publications

Full metadata record

DC FieldValue Language
dc.contributor.authorXu, Hongyanen_US
dc.contributor.authorSarkar, Bayaziden_US
dc.contributor.authorGeorge, Vargheseen_US
dc.date.accessioned2010-09-24T21:58:59Zen
dc.date.available2010-09-24T21:58:59Zen
dc.date.issued2009-03-16en_US
dc.identifier.citationBMC Res Notes. 2009 Feb 6; 2:21en_US
dc.identifier.issn1756-0500en_US
dc.identifier.pmid19284702en_US
dc.identifier.doi10.1186/1756-0500-2-21en_US
dc.identifier.urihttp://hdl.handle.net/10675.2/90en
dc.description.abstractBACKGROUND: Large-scale genome-wide association studies are promising for unraveling the genetic basis of complex diseases. Population structure is a potential problem, the effects of which on genetic association studies are controversial. The first step to systematically quantify the effects of population structure is to choose an appropriate measure of population structure for human data. The commonly used measure is Wright's FST. For a set of subpopulations it is generally assumed to be one value of FST. However, the estimates could be different for distinct loci. Since population structure is a concept at the population level, a measure of population structure that utilized the information across loci would be desirable. FINDINGS: In this study we propose an adjusted C parameter according to the sample size from each sub-population. The new measure C is based on the c parameter proposed for SNP data, which was assumed to be subpopulation-specific and common for all loci. In this study, we performed extensive simulations of samples with varying levels of population structure to investigate the properties and relationships of both measures. It is found that the two measures generally agree well. CONCLUSION: The new measure simultaneously uses the marker information across the genome. It has the advantage of easy interpretation as one measure of population structure and yet can also assess population differentiation.en_US
dc.rightsThe PMC Open Access Subset is a relatively small part of the total collection of articles in PMC. Articles in the PMC Open Access Subset are still protected by copyright, but are made available under a Creative Commons or similar license that generally allows more liberal redistribution and reuse than a traditional copyrighted work. Please refer to the license statement in each article for specific terms of use. The license terms are not identical for all articles in this subset.en_US
dc.titleA new measure of population structure using multiple single nucleotide polymorphisms and its relationship with FST.en_US
dc.typeJournal Articleen_US
dc.identifier.pmcidPMC2652468en_US
dc.contributor.corporatenameDepartment of Biostatistics and Epidemiologyen_US

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