Bioinformatics · 2016 · 32 citations · 7 references
Public HealthBiostatisticsGeneticsEpidemiologic MethodsGenomic Data AnalysisGenomicsGenome-wide Association StudiesGenotype ImputationMissing Data ComputationMissing Data HandlingMissing Data ImputationMissing Data MethodsGeneralized Linear Mixed ModelsLinear Mixed ModelsMixed Linear ModelsPopulation-specific ImputationSequence Kernel Association TestingSequence Kernel Association TestsStatistical TestingTests Of Proportional Hazards
Genotype imputation is now commonly performed following genome-wide genotyping experiments. Imputation increases the density of analyzed genotypes in the dataset, enabling fine-mapping across the genome. However, the process of imputation using the most recent publicly available reference datasets can require considerable computation power and the management of hundreds of large intermediate files. We have developed genipe, a complete genome-wide imputation pipeline which includes automatic reporting, imputed data indexing and management, and a suite of statistical tests for imputed data commonly used in genetic epidemiology (Sequence Kernel Association Test, Cox proportional hazards for survival analysis, and linear mixed models for repeated measurements in longitudinal studies). AVAILABILITY AND IMPLEMENTATION: The genipe package is an open source Python software and is freely available for non-commercial use (CC BY-NC 4.0) at https://github.com/pgxcentre/genipe Documentation and tutorials are available at http://pgxcentre.github.io/genipe CONTACT: louis-philippe.lemieux.perreault@statgen.org or marie-pierre.dube@statgen.orgSupplementary information: Supplementary data are available at Bioinformatics online.
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