netgwas (version 1.14.3)

netgwas-package: Network Based Genome Wide Association Studies

Description

The R package netgwas provides a set of tools based on undirected graphical models for accomplishing three important and interrelated goals in genetics: (1) linkage map construction, (2) reconstructing intra- and inter-chromosomal conditional interactions (linkage disequilibrium) networks, and (3) exploring high-dimensional genotype-phenotype network and genotype-phenotype- environment interactions network. The netgwas can deal with biparental species with any ploidy level. The package implemented the recent improvements both for construction of linkage maps in diploid and polyploid species in Behrouzi and Wit(2017b), and in reconstructing networks for non-Gaussian data, ordinal data, and mixed continuous and discrete data in Behrouzi and Wit (2017a). One application is to uncover epistatic interactions network, where the network captures the conditionally dependent short- and long-range linkage disequilibrium structure of a genomes and reveals aberrant marker-marker associations. In addition, Behrouzi and Wit(2017c) implemented their proposed method to explore genotype-phenotype networks where nodes are either phenotypes or genotypes, and each phenotype is connected by an edge to a genotype or a group of genotypes if there is a direct association between them, given the rest of the variables. Different phenotypes may also interconnect. The conditionally dependent relationships between markers on a genome and phenotypes is determined through Gaussian copula graphical model. We remark that environmental variables can also be included along with genotype-phenotype input data to reconstruct networks between genotypes, phenotypes, and environment variables. Beside, the package contains functions for simulation and visualization, as well as three multivariate datasets taken from literature.

Author

Pariya Behrouzi and Ernst C. Wit
Maintainers: Pariya Behrouzi

References

1. Behrouzi, P., and Wit, E. C. (2019). Detecting epistatic selection with partially observed genotype data by using copula graphical models. Journal of the Royal Statistical Society: Series C (Applied Statistics), 68(1), 141-160.
2. Behrouzi, P., and Wit, E. C. (2018). De novo construction of polyploid linkage maps using discrete graphical models. Bioinformatics.
3. Behrouzi, P., Arends, D., and Wit, E. C. (2023). netgwas: An R Package for Network-Based Genome-Wide Association Studies. The R journal, 14(4), 18-37.

Examples

if (FALSE) {
install.packages("netgwas")
library(netgwas)
}