In-depth Characterization and Analysis of Mutational Signatures (‘ICAMS’)
Analysis and visualization of experimentally elucidated mutational signatures – the kind of analysis and visualization in Boot et al., “In-depth characterization of the cisplatin mutational signature in human cell lines and in esophageal and liver tumors”, Genome Research 2018, https://doi.org/10.1101/gr.230219.117 and “Characterization of colibactin-associated mutational signature in an Asian oral squamous cell carcinoma and in other mucosal tumor types”, Genome Research 2020 https://doi.org/10.1101/gr.255620.119. ‘ICAMS’ stands for In-depth Characterization and Analysis of Mutational Signatures. ‘ICAMS’ has functions to read in variant call files (VCFs) and to collate the corresponding catalogs of mutational spectra and to analyze and plot catalogs of mutational spectra and signatures. Handles both “counts-based” and “density-based” catalogs of mutational spectra or signatures.
IMPORTANT Install the Bioconductor dependencies first:
if (!requireNamespace("BiocManager", quietly = TRUE)) {
install.packages("BiocManager")
}
BiocManager::install("BSgenome")
This may be slow; please be patient.
Afterwards, install the stable version of ICAMS from CRAN with the R command line:
To use new features in the development version, you can install ICAMS from the master branch on GitHub, which may not be stable:
if (!requireNamespace("remotes", quietly = TRUE)) {
install.packages("remotes")
}
remotes::install_github(repo = "steverozen/ICAMS", ref = "master")
Alternatively, you can download the package source of recent stable development version of ICAMS to your computer, then do:
if (!requireNamespace("remotes", quietly = TRUE)) {
install.packages("remotes")
}
remotes::install_local(path = "path-to-package-source-file-on-your-computer")
https://github.com/steverozen/ICAMS/blob/master/data-raw/ICAMS_2.3.10.pdf
You can use exported function TransformCatalog
in ICAMS to normalize the data. Please refer to the documentation and example of TransformCatalog
for more details.
If you use ICAMS in your work, please cite:
Rozen SG, Jiang NH, Boot A, Liu M, Wu Y (2021). ICAMS:In-depth Characterization and Analysis of Mutational Signatures. R package version 2.3.10, https://CRAN.R-project.org/package=ICAMS.