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)
and Behrouzi and Wit (2017) .