rapidGSEA

BACKGROUND: Gene Set Enrichment Analysis (GSEA) is a popular method to reveal
significant dependencies between predefined sets of gene symbols and observed
phenotypes by evaluating the deviation of gene expression values between cases
and controls. An established measure of inter-class deviation, the enrichment
score, is usually computed using a weighted running sum statistic over the whole
set of gene symbols. Due to the lack of analytic expressions the significance of
enrichment scores is determined using a non-parametric estimation of their null
distribution by permuting the phenotype labels of the probed patients.
Accordingly, GSEA is a time-consuming task due to the large number of required
permutations to accurately estimate the nominal p-value - a circumstance that is
even more pronounced during multiple hypothesis testing since its estimate is
lower-bounded by the inverse number of samples in permutation space. RESULTS: We
present rapidGSEA - a software suite consisting of two tools for facilitating
permutation-based GSEA: cudaGSEA and ompGSEA. cudaGSEA is a CUDA-accelerated tool
using fine-grained parallelization schemes on massively parallel architectures
while ompGSEA is a coarse-grained multi-threaded tool for multi-core CPUs.
Nominal p-value estimation of 4,725 gene sets on a data set consisting of 20,639
unique gene symbols and 200 patients (183 cases + 17 controls) each probing one
million permutations takes 19 hours on a Xeon CPU and less than one hour on a
GeForce Titan X GPU while the established GSEA tool from the Broad Institute
(broadGSEA) takes roughly 13 days. CONCLUSION: cudaGSEA outperforms broadGSEA by
around two orders-of-magnitude on a single Tesla K40c or GeForce Titan X GPU.
ompGSEA provides around one order-of-magnitude speedup to broadGSEA on a standard
Xeon CPU. The rapidGSEA suite is open-source software and can be downloaded at
https://github.com/gravitino/cudaGSEA as standalone application or package for
the R framework.

rapidGSEA: Speeding up gene set enrichment analysis on multi-core CPUs and CUDA-enabled GPUs.

rapidGSEA / cudaGSEA is a software tool for permutation-based Gene Set Enrichment Analysis (GSEA). The cudaGSEA algorithm uses  CUDA-enabled accelerators from the NVIDIA Geforce or NVIDIA Tesla series GPUs.

rapidGSEA

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