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This package is for version 3.2 of Bioconductor; for the stable, up-to-date release version, see GENESIS.

GENetic EStimation and Inference in Structured samples (GENESIS): Statistical methods for analyzing genetic data from samples with population structure and/or relatedness

Bioconductor version: 3.2

The GENESIS package provides methodology for estimating, inferring, and accounting for population and pedigree structure in genetic analyses. The current implementation provides functions to perform PC-AiR (Conomos et al., 2015) and PC-Relate (Conomos et al., In Review). PC-AiR performs a Principal Components Analysis on genome-wide SNP data for the detection of population structure in a sample that may contain known or cryptic relatedness. Unlike standard PCA, PC-AiR accounts for relatedness in the sample to provide accurate ancestry inference that is not confounded by family structure. PC-Relate uses ancestry representative principal components to adjust for population structure/ancestry and accurately estimate measures of recent genetic relatedness such as kinship coefficients, IBD sharing probabilities, and inbreeding coefficients.

Author: Matthew P. Conomos and Timothy Thornton

Maintainer: Matthew P. Conomos <mconomos at>

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HTML Population Structure and Relatedness Inference using the GENESIS Package
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biocViews BiocViews, DimensionReduction, GeneticVariability, Genetics, GenomeWideAssociation, PrincipalComponent, QualityControl, SNP, Software, StatisticalMethod
Version 2.0.1
In Bioconductor since BioC 3.1 (R-3.2) (1 year)
License GPL-3
Depends GWASTools
Imports gdsfmt
Suggests SNPRelate, RUnit, BiocGenerics, knitr
Depends On Me
Imports Me
Suggests Me
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