A multi-core R package that contains 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. For this purpose, we use conditional (in)dependence relationships between variables. 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 larger than number of sample sizes (p >> n). The computations is memory-optimized using the sparse matrix output. The package is implemented the recent developments in Behrouzi and Wit (2017) <doi:10.1111/rssc.12287> and Behrouzi and Wit (2017) <arXiv:1710.01063>.
NOTICE proper functionality of 'netgwas' requires that the 'RBGL' package is installed from 'bioconductor'; for installation instruction please refer to the 'RBGL' web page given below.

The Bayesian hierarchical model named antigen-T cell interaction estimation is to estimate the history of the immune pressure on the evolution of the tumor clones.The model is based on the estimation result from Andrew Roth (2014) <doi:10.1038/nmeth.2883>.

Tools for Working with Samples of Networks
Tools for managing large sets of network data and performing whole network analysis.
This package is focused on the network based statistic jackknife method, and
implements a framework that can be extended to other network manipulations and analyses.

person("Matteo", "Dimai", , "matteo.dimai@phd.units.it", role = c("aut", "cre"),
comment = c(ORCID = "0000-0003-1126-5234"))
Represent 'network' or 'igraph' objects whose vertices can be represented by features in an 'sf' object as a network graph surmising a 'sf' plot. Fits into 'ggplot2' grammar.
ggnetwork, igraph, network, rlang, sf, sna