PhenoMan: phenotypic data exploration, selection, management and quality control for association studies of rare and common variants

Bioinformatics
Biao LiSuzanne M Leal

Abstract

Next-generation sequencing and other high-throughput technology advances have promoted great interest in detecting associations between complex traits and genetic variants. Phenotype selection, quality control (QC) and control of confounders are crucial and can have a great impact on the ability to detect associations. Although there are programs to perform association analyses, e.g. PLINK and GenABEL, they cannot be used for comprehensive management and QC of phenotype data. To address this need PhenoMan was developed: to select individuals based on multiple phenotype criteria or population membership; control for missing covariate data; remove related individuals, duplicate samples and individuals with incorrect sex specification; recode primary traits and covariates; transform data; remove or winsorize outliers; select covariates for analysis; and create residuals. To ensure consistency and harmonization between analyses, a report is generated for every dataset. Summary statistics are also provided in graphical or text format. PhenoMan can be used for selection and manipulation of quantitative, disease and control data. Phenoman is freeware that provides approaches for efficient exploration and management of phenotype data. ...Continue Reading

References

Feb 24, 2006·European Journal of Human Genetics : EJHG·Yen-Pei Christy ChangAravinda Chakravarti
Mar 27, 2007·Bioinformatics·Yurii S AulchenkoCornelia M van Duijn
Sep 28, 2007·Nature Genetics·Matthew D MailmanStephen T Sherry
Oct 15, 2008·Human Molecular Genetics·Paul I W de BakkerBenjamin F Voight

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