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Supervised mutational signatures

Bioconductor version: Release (3.19)

Generate SuperSigs (supervised mutational signatures) from single nucleotide variants in the cancer genome. Functions included in the package allow the user to learn supervised mutational signatures from their data and apply them to new data. The methodology is based on the one described in Afsari (2021, ELife).

Author: Albert Kuo [aut, cre] , Yifan Zhang [aut], Bahman Afsari [aut], Cristian Tomasetti [aut]

Maintainer: Albert Kuo <albertkuo at>

Citation (from within R, enter citation("supersigs")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

Using supersigs HTML R Script
Reference Manual PDF


biocViews Classification, FeatureExtraction, Regression, Sequencing, Software, SomaticMutation, WholeGenome
Version 1.12.0
In Bioconductor since BioC 3.13 (R-4.1) (3 years)
License GPL-3
Depends R (>= 4.1)
Imports assertthat, caret, dplyr, tidyr, rsample, methods, rlang, utils, Biostrings, stats, SummarizedExperiment
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Suggests BSgenome.Hsapiens.UCSC.hg19, BSgenome.Hsapiens.UCSC.hg38, knitr, rmarkdown, ggplot2, testthat, VariantAnnotation
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Follow Installation instructions to use this package in your R session.

Source Package supersigs_1.12.0.tar.gz
Windows Binary
macOS Binary (x86_64) supersigs_1.12.0.tgz
macOS Binary (arm64) supersigs_1.12.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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Old Source Packages for BioC 3.19 Source Archive