Package: locStra
Type: Package
Title: Fast Implementation of (Local) Population Stratification Methods
Version: 1.9
Date: 2022-04-07
Author: Georg Hahn [aut,cre], Sharon M. Lutz [ctb], Christoph Lange [ctb]
Maintainer: Georg Hahn <ghahn@hsph.harvard.edu>
Description: Fast implementations to compute the genetic covariance matrix, the Jaccard similarity matrix, the s-matrix (the weighted Jaccard similarity matrix), and the (classic or robust) genomic relationship matrix of a (dense or sparse) input matrix (see Hahn, Lutz, Hecker, Prokopenko, Cho, Silverman, Weiss, and Lange (2020) <doi:10.1002/gepi.22356>). Full support for sparse matrices from the R-package 'Matrix'. Additionally, an implementation of the power method (von Mises iteration) to compute the largest eigenvector of a matrix is included, a function to perform an automated full run of global and local correlations in population stratification data, a function to compute sliding windows, and a function to invert minor alleles and to select those variants/loci exceeding a minimal cutoff value. New functionality in locStra allows one to extract the k leading eigenvectors of the genetic covariance matrix, Jaccard similarity matrix, s-matrix, and genomic relationship matrix via fast PCA without actually computing the similarity matrices. The fast PCA to compute the k leading eigenvectors can now also be run directly from 'bed'+'bim'+'fam' files.
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.13), Rdpack, Matrix, RSpectra, bigsnpr
RdMacros: Rdpack
LinkingTo: Rcpp, RcppEigen
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2022-04-08 00:26:41 UTC; acer
Repository: CRAN
Date/Publication: 2022-04-12 18:52:29 UTC
Built: R 4.6.0; aarch64-apple-darwin23; 2026-04-26 13:49:13 UTC; unix
Archs: locStra.so.dSYM
