netShiny - Tool for Comparison and Visualization of Multiple Networks

We developed a comprehensive tool that helps with visualization and analysis of networks with the same variables across multiple factor levels. The 'netShiny' contains most of the popular network features such as centrality measures, modularity, and other summary statistics (e.g. clustering coefficient). It also contains known tools to look at the (dis)similarities between two networks, such as pairwise distance measures between networks, set operations on the nodes of the networks, distribution of the weights of the edges and a network representing the difference between two correlation matrices. The package 'netShiny' also contains tools to perform bootstrapping and find clusters in networks. See the 'netShiny' manual for more information, documentation and examples.

Last updated 2 years ago

3.00 score 5 scripts 155 downloads

netgwas - Network-Based Genome Wide Association Studies

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>.

Last updated 8 months ago

2.65 score 3 stars 1 packages 4 scripts 366 downloads

nutriNetwork - Structure Learning with Copula Graphical Model

Statistical tool for learning the structure of direct associations among variables for continuous data, discrete data and mixed discrete-continuous data. The package is based on the copula graphical model in Behrouzi and Wit (2017) <doi:10.1111/rssc.12287>.

Last updated 1 years ago

1.00 score 1 stars 151 downloads

pcgen - Reconstruction of Causal Networks for Data with Random Genetic Effects

Implements the pcgen algorithm, which is a modified version of the standard pc-algorithm, with specific conditional independence tests and modified orientation rules. pcgen extends the approach of Valente et al. (2010) <doi:10.1534/genetics.109.112979> with reconstruction of direct genetic effects.

Last updated 6 years ago

1.00 score 105 downloads