Fast gene set enrichment analysis

By G. Korotkevich, Vladimir Sukhov, Alexey A. Sergushichev. bioRxiv, 2016

3,080 citations recorded by the source corpus.

Preranked gene set enrichment analysis (GSEA) is a widely used method for interpretation of gene expression data in terms of biological processes. Here we present FGSEA method that is able to estimate arbitrarily low GSEA P-values with a higher accuracy and much faster compared to other implementations. We also present a polynomial algorithm to calculate GSEA P-values exactly, which we use to practically confirm the accuracy of the method.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/ce7d552a58cd71ef09283f25f0ba5507bb6e641e

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In Molecular Biology

Citations in the corpus

Orchestrating single-cell analysis with Bioconductor (2019, methodology): “The first approach adapts existing gene set analysis methods originally developed for the analysis of microarray and bulk RNA-seq, such as GSEA [133] (or a fast implementation of pre-ranked GSEA in the fgsea package [137]), goseq [138], and PADOG [139], using observational weights to account for the”
Using clusterProfiler to characterize multiomics data (2024, critical): “Although many software tools are available for enrichment analysis, they all have some limitations, such as Enrichr 30 , WebGestalt 31 and fgsea 32 , which do not support full-species analysis or the latest KEGG annotation updates.”
Best practices for single-cell analysis across modalities (2023, neutral): “3).”
Single-cell landscape of peripheral and tumor-infiltrating immune cells in HPV-negative HNSCC (2025, unknown): “31,32 All genes were ranked by the product of Log2FC and p -value from the differential expression analysis to assess their condition correlation.”
The Single-Cell Landscape of Peripheral and Tumor-infiltrating Immune Cells in HPV- HNSCC (2025, unknown): “78 All genes present in the dataset were ranked using the multiplication product of Log2FC and p-value from the differential gene expression analysis, to get their correlation with the conditions.”