GSVA: gene set variation analysis for microarray and RNA-seq data

This is a fork of the rcastelo/GSVA repository. It provides an experimental version of the R package accelerated through the use of the CUDA toolkit.

🧪 Warning: This code is under active development and is not yet recommended for production use.

Most modifications are located within the src/cuda directory.

Installation

To build and run this package, you will need:

• A Linux system with an NVIDIA GPU;
• A recent version of the nvcc compiler (version 13 was used for development).

You can install the package from source using remotes:

if (!require("remotes")) install.packages("remotes")
remotes::install_github("sales-lab/GSVA")

Questions, bug reports and issues

Please submit feature requests, bug reports, or general issues via the GitHub issues tab at the top of this page.

Funding

Supported by the Chan Zuckerberg Initiative through the Essential Open Source Software for Science (EOSS) program (project "GPU-accelerated computing in Bioconductor" ,EOSS6-0000000644).