A multi-core R package that contains a set of tools based on copula graphical models for accomplishing the three interrelated goals in genetics and genomics in an unified way: (1) linkage map construction, (2) constructing linkage disequilibrium networks, and (3) exploring high-dimensional genotype-phenotype network and genotype- phenotype-environment interactions networks. The 'netgwas' package can deal with biparental inbreeding and outbreeding species with any ploidy level, namely diploid (2 sets of chromosomes), triploid (3 sets of chromosomes), tetraploid (4 sets of chromosomes) and so on. We target on high-dimensional data where number of variables p is considerably larger than number of sample sizes (p >> n). The computations is memory-optimized using the sparse matrix output. The 'netgwas' implements the methodological developments in Behrouzi and Wit (2017) <doi:10.1111/rssc.12287> and Behrouzi and Wit (2017) <doi:10.1093/bioinformatics/bty777>.
Version: 1.14.3 Depends: R (≥ 3.1.0) Imports: Matrix (≥ 1.4-1), igraph, qtl, parallel, methods, glasso, MASS, huge, tmvtnorm Suggests: testthat Published: 2024-03-19 DOI: 10.32614/CRAN.package.netgwas Author: Pariya Behrouzi [aut, cre], Ernst C. Wit [ctb] Maintainer: Pariya Behrouzi <pariya.behrouzi at gmail.com> License: GPL-3 NeedsCompilation: no Citation: netgwas citation info CRAN checks: netgwas results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=netgwas to link to this page.
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