ICAMS

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In-depth Characterization and Analysis of Mutational Signatures (‘ICAMS’)

Purpose

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” (i.e. representation as mutuations per megabase) mutational spectra or signatures.

Installation

To install the stable version from CRAN:

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 latest release version of ICAMS with the R command line:

install.packages("ICAMS")

To install the latest stable version from GitHub:

if (!requireNamespace("remotes", quietly = TRUE)) {
  install.packages("remotes")
}
remotes::install_github(repo = "steverozen/ICAMS")

Get the development version

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")

Reference manual

https://github.com/steverozen/ICAMS/blob/v3.0.6-branch/data-raw/ICAMS_3.0.6.pdf

Frequently asked questions

How to do normalization for “counts-based” catalogs of mutational spectra or signatures to account for differing abundances of the source sequence of the mutations?

You can use exported function TransformCatalog in ICAMS to normalize the data. Please refer to the documentation and example of TransformCatalog for more details.

Citing ICAMS

If you use ICAMS in your work, please cite:

Rozen SG, Jiang NH, Boot A, Liu M, Wu Y, Huang MN, Chang JG (2021). ICAMS:In-depth Characterization and Analysis of Mutational Signatures. R package version 3.0.6, https://CRAN.R-project.org/package=ICAMS.

steverozen / ICAMS

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