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dc.contributor.author Friedrichs, Stefanie
dc.contributor.author Malzahn, Dörthe
dc.contributor.author Pugh, Elizabeth W
dc.contributor.author Almeida, Marcio
dc.contributor.author Liu, Xiao Q
dc.contributor.author Bailey, Julia N
dc.date.accessioned 2016-02-04T14:58:03Z
dc.date.available 2016-02-04T14:58:03Z
dc.date.issued 2016-02-03
dc.identifier.citation BMC Genetics. 2016 Feb 03;17(Suppl 2):8
dc.identifier.uri http://dx.doi.org/10.1186/s12863-015-0313-x
dc.identifier.uri http://hdl.handle.net/1993/31126
dc.description.abstract Abstract High-density genetic marker data, especially sequence data, imply an immense multiple testing burden. This can be ameliorated by filtering genetic variants, exploiting or accounting for correlations between variants, jointly testing variants, and by incorporating informative priors. Priors can be based on biological knowledge or predicted variant function, or even be used to integrate gene expression or other omics data. Based on Genetic Analysis Workshop (GAW) 19 data, this article discusses diversity and usefulness of functional variant scores provided, for example, by PolyPhen2, SIFT, or RegulomeDB annotations. Incorporating functional scores into variant filters or weights and adjusting the significance level for correlations between variants yielded significant associations with blood pressure traits in a large family study of Mexican Americans (GAW19 data set). Marker rs218966 in gene PHF14 and rs9836027 in MAP4 significantly associated with hypertension; additionally, rare variants in SNUPN significantly associated with systolic blood pressure. Variant weights strongly influenced the power of kernel methods and burden tests. Apart from variant weights in test statistics, prior weights may also be used when combining test statistics or to informatively weight p values while controlling false discovery rate (FDR). Indeed, power improved when gene expression data for FDR-controlled informative weighting of association test p values of genes was used. Finally, approaches exploiting variant correlations included identity-by-descent mapping and the optimal strategy for joint testing rare and common variants, which was observed to depend on linkage disequilibrium structure.
dc.rights info:eu-repo/semantics/openAccess
dc.title Filtering genetic variants and placing informative priors based on putative biological function
dc.type Journal Article
dc.type info:eu-repo/semantics/article
dc.language.rfc3066 en
dc.rights.holder Friedrichs et al.
dc.date.updated 2016-02-03T17:04:17Z


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