graphsim version 1.0.4

Minor update to pass CRAN checks

• updates citation for retain on CRAN

• avoids deprecated use of S3 methods

Full Changelog: 1.0.3...v1.0.4

graphsim version 1.0.3

Minor update to pass CRAN checks

• removed imports for unused packages

• removed dependency on deprecated sparse matrices

• correct links in citations and vignettes

Full Changelog: v1.0.2...1.0.3

graphsim version 1.0.2

Updates maintainer contact details.

• resolves vignette formatting #11

• passes updated CRAN checks (links updated)

Version 1.0.1

graphsim version 1.0.1

• 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)

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

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

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)

See JOSS review for details.

Version 0.1.2

• Initial CRAN release

• Unit testing for all functions

• Full documentation for all functions

• Checking for compatible inputs

• Passing layout parameters to plotting function

Version 0.1.1

Full release with vignettes and documentation. Meets CRAN submission criteria. Supplementary material for manuscript submitted for peer-review.

Version 0.1.0

Initial Release

Supporting manuscript in preparation to describe this software (an R package)