Show simple item record

dc.contributor.authorYan, Aimin
dc.contributor.authorLaird, Nan M.
dc.contributor.authorLi, Cheng
dc.date.accessioned2012-04-20T15:43:50Z
dc.date.issued2011
dc.identifier.citationYan, Aimin, Nan M. Laird, and Cheng Li. 2011. Identifying rare variants using a Bayesian regression approach. BMC Proceedings 5(Suppl 9): S99.en_US
dc.identifier.issn1753-6561en_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:8605302
dc.description.abstractRecent advances in next-generation sequencing technologies have made it possible to generate large amounts of sequence data with rare variants in a cost-effective way. Statistical methods that test variants individually are underpowered to detect rare variants, so it is desirable to perform association analysis of rare variants by combining the information from all variants. In this study, we use a Bayesian regression method to model all variants simultaneously to identify rare variants in a data set from Genetic Analysis Workshop 17. We studied the association between the quantitative risk traits Q1, Q2, and Q4 and the single-nucleotide polymorphisms and identified several positive single-nucleotide polymorphisms for traits Q1 and Q2. However, the model also generated several apparent false positives and missed many true positives, suggesting that there is room for improvement in this model.en_US
dc.language.isoen_USen_US
dc.publisherBioMed Centralen_US
dc.relation.isversionofdoi://10.1186/1753-6561-5-S9-S99en_US
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287941/pdf/en_US
dash.licenseLAA
dc.titleIdentifying Rare Variants Using a Bayesian Regression Approachen_US
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden_US
dc.relation.journalBMC Proceedingsen_US
dash.depositing.authorYan, Aimin
dc.date.available2012-04-20T15:43:50Z
dc.identifier.doi10.1186/1753-6561-5-S9-S99*
dash.contributor.affiliatedYan, Aimin
dash.contributor.affiliatedLaird, Nan
dash.contributor.affiliatedLi, Cheng


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record