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dc.contributor.authorLiu, Dajiang J.en_US
dc.contributor.authorPeloso, Gina M.en_US
dc.contributor.authorZhan, Xiaoweien_US
dc.contributor.authorHolmen, Oddgeir L.en_US
dc.contributor.authorZawistowski, Matthewen_US
dc.contributor.authorFeng, Shuangen_US
dc.contributor.authorNikpay, Majiden_US
dc.contributor.authorAuer, Paul L.en_US
dc.contributor.authorGoel, Anujen_US
dc.contributor.authorZhang, Heen_US
dc.contributor.authorPeters, Ulrikeen_US
dc.contributor.authorFarrall, Martinen_US
dc.contributor.authorOrho-Melander, Marjuen_US
dc.contributor.authorKooperberg, Charlesen_US
dc.contributor.authorMcPherson, Ruthen_US
dc.contributor.authorWatkins, Hughen_US
dc.contributor.authorWiller, Cristen J.en_US
dc.contributor.authorHveem, Kristianen_US
dc.contributor.authorMelander, Olleen_US
dc.contributor.authorKathiresan, Sekaren_US
dc.contributor.authorAbecasis, Gonçalo R.en_US
dc.date.accessioned2014-09-08T15:37:49Z
dc.date.issued2014en_US
dc.identifier.citationLiu, D. J., G. M. Peloso, X. Zhan, O. L. Holmen, M. Zawistowski, S. Feng, M. Nikpay, et al. 2014. “Meta-Analysis of Gene Level Tests for Rare Variant Association.” Nature genetics 46 (2): 200-204. doi:10.1038/ng.2852. http://dx.doi.org/10.1038/ng.2852.en
dc.identifier.issn1061-4036en
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:12785981
dc.description.abstractThe vast majority of connections between complex disease and common genetic variants were identified through meta-analysis, a powerful approach that enables large sample sizes while protecting against common artifacts due to population structure, repeated small sample analyses, and/or limitations with sharing individual level data. As the focus of genetic association studies shifts to rare variants, genes and other functional units are becoming the unit of analysis. Here, we propose and evaluate new approaches for performing meta-analysis of rare variant association tests, including burden tests, weighted burden tests, variable threshold tests and tests that allow variants with opposite effects to be grouped together. We show that our approach retains useful features of single variant meta-analytic approaches and demonstrate its utility in a study of blood lipid levels in ∼18,500 individuals genotyped with exome arrays.en
dc.language.isoen_USen
dc.relation.isversionofdoi:10.1038/ng.2852en
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3939031/pdf/en
dash.licenseLAAen_US
dc.titleMeta-Analysis of Gene Level Tests for Rare Variant Associationen
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden
dc.relation.journalNature geneticsen
dash.depositing.authorPeloso, Gina M.en_US
dc.date.available2014-09-08T15:37:49Z
dc.identifier.doi10.1038/ng.2852*
dash.authorsorderedfalse
dash.contributor.affiliatedPeloso, Gina M


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