Show simple item record

dc.contributor.authorBhatia, Gaurav
dc.contributor.authorPatterson, Nick
dc.contributor.authorSankararaman, Sriram
dc.contributor.authorPrice, Alkes L.
dc.date.accessioned2014-03-17T16:08:01Z
dc.date.available2014-03-17T16:08:01Z
dc.date.issued2013-07
dc.date.submitted2013-07
dc.identifier.issn1088-9051
dc.identifier.urihttp://hdl.handle.net/1721.1/85674
dc.description.abstractIn a pair of seminal papers, Sewall Wright and Gustave Malécot introduced F[subscript ST] as a measure of structure in natural populations. In the decades that followed, a number of papers provided differing definitions, estimation methods, and interpretations beyond Wright's. While this diversity in methods has enabled many studies in genetics, it has also introduced confusion regarding how to estimate F[subscript ST] from available data. Considering this confusion, wide variation in published estimates ofF[subscript ST] for pairs of HapMap populations is a cause for concern. These estimates changed—in some cases more than twofold—when comparing estimates from genotyping arrays to those from sequence data. Indeed, changes in F[subscript ST] from sequencing data might be expected due to population genetic factors affecting rare variants. While rare variants do influence the result, we show that this is largely through differences in estimation methods. Correcting for this yields estimates of F[subscript ST] that are much more concordant between sequence and genotype data. These differences relate to three specific issues: (1) estimating F[subscript ST] for a single SNP, (2) combining estimates of F[subscript ST] across multiple SNPs, and (3) selecting the set of SNPs used in the computation. Changes in each of these aspects of estimation may result in F[subscript ST] estimates that are highly divergent from one another. Here, we clarify these issues and propose solutions.en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant T32 HG002295)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant R03 HG006170)en_US
dc.language.isoen_US
dc.publisherCold Spring Harbor Laboratory Pressen_US
dc.relation.isversionofhttp://dx.doi.org/10.1101/gr.154831.113en_US
dc.rightsCreative Commons Attribution-Noncommericalen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/en_US
dc.sourceCold Spring Harbor Laboratory Pressen_US
dc.titleEstimating and interpreting F[subscript ST]: The impact of rare variantsen_US
dc.typeArticleen_US
dc.identifier.citationBhatia, G., N. Patterson, S. Sankararaman, and A. L. Price. “Estimating and Interpreting FST: The Impact of Rare Variants.” Genome Research 23, no. 9 (September 1, 2013): 1514–1521.en_US
dc.contributor.departmentWhitaker College of Health Sciences and Technologyen_US
dc.contributor.departmentHarvard University--MIT Division of Health Sciences and Technologyen_US
dc.contributor.mitauthorBhatia, Gauraven_US
dc.relation.journalGenome Researchen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsBhatia, G.; Patterson, N.; Sankararaman, S.; Price, A. L.en_US
mit.licensePUBLISHER_CCen_US
mit.metadata.statusComplete


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record