sigminer: Capture Genomic Variation Signatures using Non-Negative Matrix Factorization

Contains functions for identification of copy number signatures (Geoffrey et al. (2018) <doi:10.1038/s41588-018-0179-8>) and mutation signatures (Alexandrov et al. (2018) <doi:10.1038/nature12477>) by non-negative matrix factorization, signature analysis and visualization. It can be used to capture signatures of genomic variation, compare genotype or phenotype features of different signatures and thus uncover the relationship between the mechanism of genomic variation and phenotypes in cancer.

Version: 0.1.9
Depends: R (≥ 3.5)
Imports: cluster, corrplot, cowplot, data.table, doParallel, dplyr, flexmix, foreach, ggplot2, maftools, methods, NMF, RColorBrewer, tidyr, magrittr, purrr
Suggests: BSgenome.Hsapiens.UCSC.hg19, cowsay, ggpubr, knitr, rmarkdown, covr, testthat, prettydoc, pheatmap
Published: 2019-04-25
Author: Shixiang Wang ORCID iD [aut, cre], Geoffrey Macintyre [ctb], Xue-Song Liu [ctb]
Maintainer: Shixiang Wang <w_shixiang at 163.com>
BugReports: https://github.com/ShixiangWang/sigminer/issues
License: MIT + file LICENSE
URL: https://github.com/ShixiangWang/sigminer
NeedsCompilation: no
Materials: README NEWS
CRAN checks: sigminer results

Downloads:

Reference manual: sigminer.pdf
Vignettes: Usage documentation
Package source: sigminer_0.1.9.tar.gz
Windows binaries: r-devel: sigminer_0.1.9.zip, r-release: sigminer_0.1.9.zip, r-oldrel: sigminer_0.1.9.zip
OS X binaries: r-release: not available, r-oldrel: not available

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