The R package sigvar implements signature variability analysis, a framework for the analysis of mutational signature activities within and across cancer samples. This R package accompanies the paper “Variability of mutational signatures is a footprint of carcinogens’’ by Morrison et al.; please refer to the paper for more details on the methods presented in this package.
The sigvar package contains two core functions to perform signature variability analysis:
-
sigvar: Compute the within-sample diversity and across-sample heterogeneity of mutational signature activity in one or multiple populations of samples -
sigboot: Use bootstrapping to statistically compare the within-sample diversity and across-sample heterogeneity of the mutational signature activity between two or more groups of samples
sigvar also includes accessory functions for the visualization of mutational signature data, such as:
-
plot_SBS_spectrum: Plot the SBS mutational spectrum of one or more samples of mutational signatures -
plot_signature_prop: Plot the relative activities of mutational signatures in each sample as a stacked bar plot -
plot_dots: Plot the mean mutational signature contributions of one or more groups of samples
You can install the development version of sigvar from GitHub with:
install.packages("devtools") # run only if devtools not already installed
devtools::install_github("MaikeMorrison/sigvar", dependencies = TRUE, build_vignettes = TRUE)Installation time ranges from 1 to 5 minutes depending on whether dependencies also need to be installed. Run time is expected to be a few minutes on a typical desktop computer.
The package has been tested on R version 4.1.2 on a Redhat Linux platform and a Windows 10 Pro platform. The package is available under the MIT license.
A tutorial on the usage of sigvar is available in the tutorial
vignette, which is available at this
link or via the
following R code after package installation:
vignette("tutorial", package = "sigvar")