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BACKGROUND: Over the last few years, genome-wide association (GWA) studies became a tool of choice for the identification of loci associated with complex traits. Currently, imputed single nucleotide polymorphisms (SNP) data are frequently used in GWA analyzes. Correct analysis of imputed data calls for the implementation of specific methods which take genotype imputation uncertainty into account. RESULTS: We developed the ProbABEL software package for the analysis of genome-wide imputed SNP data and quantitative, binary, and time-till-event outcomes under linear, logistic, and Cox proportional hazards models, respectively. For quantitative traits, the package also implements a fast two-step mixed model-based score test for association in samples with differential relationships, facilitating analysis in family-based studies, studies performed in human genetically isolated populations and outbred animal populations. CONCLUSIONS: ProbABEL package provides fast efficient way to analyze imputed data in genome-wide context and will facilitate future identification of complex trait loci.

Original publication

DOI

10.1186/1471-2105-11-134

Type

Journal article

Journal

BMC Bioinformatics

Publication Date

16/03/2010

Volume

11

Keywords

Genome-Wide Association Study, Genotype, Humans, Models, Genetic, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Software