Update citation to reflect acceptance at JOSS
Update documentation (package help page, links and cross-references)
Critical changes to vignettes to reduce build time (required for regular CRAN checks)

Assets 2

06 Jul 08:12

TomKellyGenetics

1.0.0-joss

7b6077b

graphsim: An R package for simulating gene expression data from graph structures of biological pathways Pre-release

Pre-release

Peer-reviewed software and manuscript. See the JOSS review issue for details:
openjournals/joss-reviews#2161

This package provides functions to develop simulated continuous data (e.g., gene expression) from a sigma covariance matrix derived from a graph structure in 'igraph' objects. Intended to extend 'mvtnorm' to take 'igraph' structures rather than sigma matrices as input. This allows the use of simulated data that correctly accounts for pathway relationships and correlations. Here we present a versatile statistical framework to simulate correlated gene expression data from biological pathways, by sampling from a multivariate normal distribution derived from a graph structure. This package allows the simulation of biological pathways from a graph structure based on a statistical model of gene expression, such as simulation of expression profiles that of log-transformed and normalised data from microarray and RNA-Seq data.

Zenodo doi: 105281/zenodo.3931288

Assets 4

02 Jul 02:43

TomKellyGenetics

v1.0.0

a7f1965

Version 1.0.0

Major stable release: note changes to results are possible! (legacy code should run without breaking)
Expanded documentation and examples (consolidate into fewer vignettes for clarity)
Resolves errors handling inhibiting edges
Efficiently compute a state matrix from a vector of edge properties from paths
Enables passing "sd" (standard deviation) to alter covariance of Sigma matrix
Adds methods for computing using Laplacian matrices
Adds function to compute simulations directly from an adjacency matrix
Migrates computing states to sigma (these matrices include inhibitions)