Package: GENESIS
Type: Package
Title: GENetic EStimation and Inference in Structured samples
        (GENESIS): Statistical methods for analyzing genetic data from
        samples with population structure and/or relatedness
Version: 2.43.0
Date: 2025-01-31
Authors@R: c(
  person(c("Matthew", "P."), "Conomos", role = c("aut")),
  person(c("Stephanie", "M."), "Gogarten", email = "sdmorris@uw.edu", role = c("aut", "cre")),
  person("Lisa", "Brown", role = "aut"),
  person("Han", "Chen", role = "aut"),
  person("Thomas", "Lumley", role = "aut"),
  person("Kenneth", "Rice", role = "aut"),
  person("Tamar", "Sofer", role = "aut"),
  person("Adrienne", "Stilp", role = "aut"),
  person("Timothy", "Thornton", role = "aut"),
  person("Chaoyu", "Yu", role = "aut"))
Description: 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.
License: GPL-3
URL: https://github.com/UW-GAC/GENESIS
Depends:
Imports: Biobase, BiocGenerics, BiocParallel, GWASTools, gdsfmt,
        GenomicRanges, IRanges, S4Vectors, SeqArray, SeqVarTools,
        SNPRelate, data.table, graphics, grDevices, igraph, Matrix,
        methods, reshape2, stats, utils
Suggests: CompQuadForm, COMPoissonReg, poibin, SPAtest, survey,
        testthat, BiocStyle, knitr, rmarkdown, GWASdata, dplyr,
        ggplot2, GGally, RColorBrewer,
        TxDb.Hsapiens.UCSC.hg19.knownGene, GenomeInfoDb
VignetteBuilder: knitr
biocViews: SNP, GeneticVariability, Genetics, StatisticalMethod,
        DimensionReduction, PrincipalComponent, GenomeWideAssociation,
        QualityControl, BiocViews
NeedsCompilation: yes
RoxygenNote: 7.3.3
Config/pak/sysreqs: cmake libglpk-dev make libicu-dev libxml2-dev
        libx11-dev zlib1g-dev
Repository: https://bioc.r-universe.dev
Date/Publication: 2026-04-28 12:40:50 UTC
RemoteUrl: https://github.com/bioc/GENESIS
RemoteRef: HEAD
RemoteSha: df969fc093b79f55b5cebe6107f07c17d2f16de4
Packaged: 2026-05-18 10:25:59 UTC; root
Author: Matthew P. Conomos [aut],
  Stephanie M. Gogarten [aut, cre],
  Lisa Brown [aut],
  Han Chen [aut],
  Thomas Lumley [aut],
  Kenneth Rice [aut],
  Tamar Sofer [aut],
  Adrienne Stilp [aut],
  Timothy Thornton [aut],
  Chaoyu Yu [aut]
Maintainer: Stephanie M. Gogarten <sdmorris@uw.edu>
Built: R 4.6.0; x86_64-w64-mingw32; 2026-05-18 10:33:31 UTC; windows
Archs: x64
