Package: supersigs 1.15.0

Albert Kuo

supersigs: Supervised mutational signatures

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).

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

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supersigs.pdf |supersigs.html✨
supersigs/json (API)
NEWS

# Install 'supersigs' in R:

install.packages('supersigs', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/tomasettilab/supersigs/issues

Pkgdown:https://tomasettilab.github.io

Datasets:

example_dt - Example dataset of mutations
supersig_ls - Trained SuperSigs from TCGA

On BioConductor:supersigs-1.15.0(bioc 3.21)supersigs-1.14.0(bioc 3.20)

featureextraction classification regression sequencing wholegenome somaticmutation

4.78 score 3 stars 3 scripts 340 downloads 6 exports 106 dependencies

Last updated 2 months agofrom:4d9190b169. Checks:OK: 7. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Dec 18 2024
R-4.5-win	OK	Dec 18 2024
R-4.5-linux	OK	Dec 18 2024
R-4.4-win	OK	Dec 18 2024
R-4.4-mac	OK	Dec 18 2024
R-4.3-win	OK	Dec 18 2024
R-4.3-mac	OK	Dec 18 2024

Exports:get_signature make_matrix partial_signature predict_signature process_vcf simplify_signature

Dependencies:abind askpass assertthat Biobase BiocGenerics Biostrings caret class cli clock codetools colorspace cpp11 crayon curl data.table DelayedArray diagram digest dplyr e1071 fansi farver foreach furrr future future.apply generics GenomeInfoDb GenomeInfoDbData GenomicRanges ggplot2 globals glue gower gtable hardhat httr ipred IRanges isoband iterators jsonlite KernSmooth labeling lattice lava lifecycle listenv lubridate magrittr MASS Matrix MatrixGenerics matrixStats mgcv mime ModelMetrics munsell nlme nnet numDeriv openssl parallelly pillar pkgconfig plyr pROC prodlim progressr proxy purrr R6 RColorBrewer Rcpp recipes reshape2 rlang rpart rsample S4Arrays S4Vectors scales shape slider SparseArray SQUAREM stringi stringr SummarizedExperiment survival sys tibble tidyr tidyselect timechange timeDate tzdb UCSC.utils utf8 vctrs viridisLite warp withr XVector zlibbioc

Using supersigs

Rendered fromsupersigs.Rmdusingknitr::rmarkdownon Dec 18 2024.

Last update: 2021-04-05
Started: 2020-02-03

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Example dataset of mutations	example_dt
Function to obtain a SuperSig	get_signature
Function to transform mutations into "matrix" format	make_matrix
Function to remove the contribution of a SuperSig	partial_signature
Function to predict using SuperSig object	predict_signature
Function to transform VCF object into "matrix" format	process_vcf
Function to simplify signature representation into interpretable labels for visualization purposes	simplify_signature
Trained SuperSigs from TCGA	supersig_ls
An S4 class for SuperSig	SuperSig SuperSig-class