FGSEA statistics

Tool stats & trends

Looking to identify usage trends or leading experts?

Protocols

FGSEA specifications

Information


Unique identifier OMICS_16449
Name FGSEA
Alternative name Fast Gene Set Enrichment Analysis
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Computer skills Advanced
Stability Stable
Requirements
R
Maintained Yes

Download


download.png
github.png

Versioning


No version available

Documentation


Maintainer


  • person_outline Alexey Sergushichev

Publication for Fast Gene Set Enrichment Analysis

FGSEA citations

 (4)
library_books

Distinct epigenetic landscapes underlie the pathobiology of pancreatic cancer subtypes

2018
Nat Commun
PMCID: 5958058
PMID: 29773832
DOI: 10.1038/s41467-018-04383-6

[…] nts were normalized using RPKM. Student’s t-tests were performed to test for differentially expressed genes (list is given in Supplementary Table ) between the siMET basal and scramble basal samples. Fgsea enrichment tests were performed based on Pvalues of the differential analysis of basal siMET vs. basal control samples, and by using MsigDB database and the described open resource. For qPCR, to […]

call_split

Histone H3.3 sub variant H3mm7 is required for normal skeletal muscle regeneration

2018
Nat Commun
PMCID: 5895627
PMID: 29643389
DOI: 10.1038/s41467-018-03845-1
call_split See protocol

[…] hree conditions (H3.3+, H3mm7+, and WT), were extracted by fitting the model without interaction as performed in C2C12 cells. The preranked GSEA with the log2FC values of DEGs was performed using the fgsea package and visualized using the DOSE package in R. The regularized log-transformed (rlog function in DESeq2) read counts of genes were utilized as the gene expression level in the following ana […]

call_split

The chromatin remodeling factor ISW 1 integrates organismal responses against nuclear and mitochondrial stress

2017
Nat Commun
PMCID: 5703887
PMID: 29180639
DOI: 10.1038/s41467-017-01903-8
call_split See protocol

[…] ch treatment, all expressed genes were ordered by decreasing fold change based on the differential expression analysis. For each analysis and GO category, we performed 100,000 permutations using the “fgsea” option, a minimum gene set size of 5, and a maximum of 1000. False discovery rate-adjusted P-values were calculated using the Benjamini–Hochberg method. […]

library_books

The conjugated antimetabolite 5 FdU ECyd and its cellular and molecular effects on platinum sensitive vs. resistant ovarian cancer cells in vitro

2017
Oncotarget
PMCID: 5652753
PMID: 29100359
DOI: 10.18632/oncotarget.20260

[…] DAVID Bioinformatics Resource []. Secondly, the R package gage was applied on the log2 fold-changes (log2 FC) of all genes for the different conditions using KEGG pathways []. Thirdly, the R package fgsea was used for a full gene set enrichment analysis. Log10 (p-value) * signum(log2 FC) was used as rank function and 100,000 permutations for p-value calculation of pathway enrichments. […]

Citations

Looking to check out a full list of citations?

FGSEA institution(s)
Computer Technologies Department, ITMO University, Saint Petersburg, Russia
FGSEA funding source(s)
This work was supported by Government of Russian Federation Grant 074-U01.

FGSEA reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review FGSEA