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

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, Gen Epi) and PC-Relate (Conomos et al., 2016, AJHG). 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. Additionally, functions are provided to perform efficient variance component estimation and mixed model association testing for both quantitative and binary phenotypes.

Package details

AuthorMatthew P. Conomos, Stephanie M. Gogarten, Lisa Brown, Han Chen, Thomas Lumley, Ken Rice, Tamar Sofer, Timothy Thornton, Chaoyu Yu
Bioconductor views BiocViews DimensionReduction GeneticVariability Genetics GenomeWideAssociation PrincipalComponent QualityControl SNP StatisticalMethod
MaintainerStephanie M. Gogarten <>
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:

Try the GENESIS package in your browser

Any scripts or data that you put into this service are public.

GENESIS documentation built on April 29, 2020, 4:26 a.m.