/mtor-rcc

Analysis of TCGA/IMPACT datasets, and mTOR mutation status across cancer types

Primary LanguageR

mtor-rcc

Analysis of TCGA datasets, and mTOR mutations across cancer types

Dependencies

The dev environment can be reproduced using conda env create -f mtor-rcc.yml.

Additional R packages required can be installed via BiocManager:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("maftools")
BiocManager::install("TCGAbiolinks")
BiocManager::install("PoisonAlien/TCGAmutations")

Run

Run the analysis with the following:

conda activate mtor-rcc snakemake -s Snakefile -j1

The flag -j1 tells snakemake to parallelize over one job. In Snakefile, taskset is used to restrict the cores that MutSigCV is allowed to run on (27,28,29,30) - you may wish to customize this to your machine/compute environment.

Results

  • MutSigCV results are by default output to the directory mutsigcv_results/<sample set>/<source>
  • Plots are output to plots/<sample set>/<source>