Installation

Download git-lfs: https://git-lfs.github.com/

Install using devtools

To calculate signature likelihoods and Sig3 detection the following is sufficient

1. Install Bioconductor packages

packages <- c("BSgenome",
    "BSgenome.Hsapiens.UCSC.hg19",
    "BSgenome.Hsapiens.UCSC.hg38",
    "GenomicRanges",
    "IRanges",
    "VariantAnnotation")

if(getRversion() >= "3.6.0"){
  if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager", repos = "http://cran.us.r-project.org")
  BiocManager::install(packages)
}
if(getRversion() < "3.6.0" & getRversion() >= "3.5.0"){
  source("https://bioconductor.org/biocLite.R")
  biocLite(packages)
}

2. Install SigMA

install.packages("devtools")
devtools::install_github("parklab/SigMA")

library(SigMA)

Local installation

To download the bed files for MSI regions, do a local installation instead.

Clone SigMA to your computer, run the installation script:

git lfs install --local --skip-smudge
git clone https://github.com/parklab/SigMA
git lfs pull

cd SigMA
Rscript install.R

To make sure it was installed correctly try: Rscript examples/test.R This should produce the datafile with 96-dimensional spectra and run SigMA for two files.