MixupMapper: correcting sample mix-ups in genome-wide datasets increases power to detect small genetic effects | Zendy

Harm-Jan Westra | Zendy; Ritsert C. Jansen | Zendy; Rudolf S.N. Fehrmann | Zendy; Gerard J. te Meerman | Zendy; David A. van Heel | Zendy; Cisca Wijmenga | Zendy; Lude Franke | Zendy

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MixupMapper: correcting sample mix-ups in genome-wide datasets increases power to detect small genetic effects

Author(s) -

Harm-Jan Westra,

Ritsert C. Jansen,

Rudolf S.N. Fehrmann,

Gerard J. te Meerman,

David A. van Heel,

Cisca Wijmenga,

Lude Franke

Publication year - 2011

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btr323

Subject(s) - genotyping , heritability , sample size determination , sample (material) , biology , genome , computational biology , expression quantitative trait loci , quantitative trait locus , genome wide association study , genetics , genomics , computer science , statistics , gene , genotype , single nucleotide polymorphism , mathematics , chemistry , chromatography

Sample mix-ups can arise during sample collection, handling, genotyping or data management. It is unclear how often sample mix-ups occur in genome-wide studies, as there currently are no post hoc methods that can identify these mix-ups in unrelated samples. We have therefore developed an algorithm (MixupMapper) that can both detect and correct sample mix-ups in genome-wide studies that study gene expression levels.

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