Sigminer: Mutational Signature Analysis and Visualization in R <img src="man/figures/logo.png" alt="logo" align="right" height="140" width="120"/>

:bar_chart: Overview

The cancer genome is shaped by various mutational processes over its
lifetime, stemming from exogenous and cell-intrinsic DNA damage, and
error-prone DNA replication, leaving behind characteristic mutational
spectra, termed mutational signatures. This package, sigminer,
helps users to extract, analyze and visualize signatures from genome
alteration records, thus providing new insight into cancer study.

For pipeline tool, please see its co-evolutionary CLI
sigflow.

SBS signatures:

Copy number signatures:

DBS signatures:

INDEL (i.e. ID) signatures:

Genome rearrangement signatures:

:airplane: Features

supports a standard de novo pipeline for identification of 5
types of signatures: copy number, SBS, DBS, INDEL and RS (genome
rearrangement signature).
supports quantify exposure for one sample based on known signatures.
supports association and group analysis and visualization for
signatures.
supports two types of signature exposures: relative exposure (relative
contribution of signatures in each sample) and absolute exposure
(estimated variation records of signatures in each sample).
supports basic summary and visualization for profile of mutation
(powered by maftools) and copy number.
supports parallel computation by R packages foreach, future
and NMF.
efficient code powered by R packages data.table and tidyverse.
elegant plots powered by R packages ggplot2, ggpubr,
cowplot and patchwork.
well tested by R package testthat and documented by R package
roxygen2, roxytest, pkgdown, and etc. for both reliable
and reproducible research.

:arrow_double_down: Installation

You can install the stable release of sigminer from CRAN with:

r
install.packages("BiocManager")
BiocManager::install("sigminer", dependencies = TRUE)

You can install the development version of sigminer from Github
with:

r
BiocManager::install("ShixiangWang/sigminer", dependencies = TRUE)

You can also install sigminer from conda bioconda channel with

sh
# Please note version number of the bioconda release

# You can install an individual environment firstly with
# conda create -n sigminer
# conda activate sigminer
conda install -c bioconda -c conda-forge r-sigminer

:beginner: Usage

A complete documentation of sigminer can be read online at
https://shixiangwang.github.io/sigminer-book/. All functions are well
organized and documented at
https://shixiangwang.github.io/sigminer/reference/index.html. For
usage of a specific function fun, run ?fun in your R console to see
its documentation.

:question: QA

How to install the `copynumber` package

For some extra features provided by sigminer, copynumber package
is required. Due to the removal of the copynumber package from Bioc,
I had to remove it from the dependencies in v2.2.0. You can install the
package from https://github.com/shixiangwang/copynumber/. It is
generally recommended as I have added some features, although other
forks of this package exist on GitHub.

r
remotes::install_github("ShixiangWang/copynumber")

:paperclip: Citation

If you use sigminer in academic field, please at least cite one of
the following papers.

Wang S, Li H, Song M, Tao Z, Wu T, He Z, et al. (2021) Copy number
signature analysis tool and its application in prostate cancer reveals
distinct mutational processes and clinical outcomes. PLoS Genet 17(5):
e1009557. https://doi.org/10.1371/journal.pgen.1009557
Wang, S., Tao, Z., Wu, T., & Liu, X. S. (2021). Sigflow: an
automated and comprehensive pipeline for cancer genome mutational
signature analysis. Bioinformatics, 37(11), 1590-1592.
https://doi.org/10.1093/bioinformatics/btaa895
Ziyu Tao, Shixiang Wang, Chenxu Wu, Tao Wu, Xiangyu Zhao, Wei Ning,
Guangshuai Wang, Jinyu Wang, Jing Chen, Kaixuan Diao, Fuxiang Chen,
Xue-Song Liu, The repertoire of copy number alteration signatures in
human cancer, Briefings in Bioinformatics, 2023, bbad053.
https://doi.org/10.1093/bib/bbad053

:arrow_down: Download Stats

:page_with_curl: References

Please properly cite the following references when you are using any
corresponding features. The references are also listed in the function
documentation. Very thanks to the works, sigminer cannot be created
without the giants.

Mayakonda, Anand, et al. “Maftools: efficient and comprehensive
analysis of somatic variants in cancer.” Genome research 28.11
(2018): 1747-1756.
Gaujoux, Renaud, and Cathal Seoighe. “A Flexible R Package for
Nonnegative Matrix Factorization.”” BMC Bioinformatics 11, no. 1
(December 2010).
H. Wickham. ggplot2: Elegant Graphics for Data Analysis.
Springer-Verlag New York, 2016.
Kim, Jaegil, et al. “Somatic ERCC2 mutations are associated with a
distinct genomic signature in urothelial tumors.” Nature genetics
48.6 (2016): 600.
Alexandrov, Ludmil B., et al. “Deciphering signatures of mutational
processes operative in human cancer.” Cell reports 3.1 (2013):
246-259.
Degasperi, Andrea, et al. “A practical framework and online tool for
mutational signature analyses show intertissue variation and driver
dependencies.” Nature cancer 1.2 (2020): 249-263.
Alexandrov, Ludmil B., et al. “The repertoire of mutational
signatures in human cancer.” Nature 578.7793 (2020): 94-101.
Macintyre, Geoff, et al. “Copy number signatures and mutational
processes in ovarian carcinoma.” Nature genetics 50.9 (2018): 1262.
Tan, Vincent YF, and Cédric Févotte. “Automatic relevance
determination in nonnegative matrix factorization with the/spl
beta/-divergence.” IEEE Transactions on Pattern Analysis and Machine
Intelligence 35.7 (2012): 1592-1605.
Bergstrom EN, Huang MN, Mahto U, Barnes M, Stratton MR, Rozen SG,
Alexandrov LB: SigProfilerMatrixGenerator: a tool for visualizing
and exploring patterns of small mutational events. BMC Genomics
2019, 20:685
https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-019-6041-2

:page_facing_up: LICENSE

The software is made available for non commercial research purposes only
under the
MIT.
However, notwithstanding any provision of the MIT License, the software
currently may not be used for commercial purposes without explicit
written permission after contacting patents’ authors.

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