📊 A universal enrichment tool for interpreting omics data
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Updated
Aug 26, 2024 - R
📊 A universal enrichment tool for interpreting omics data
Gene Set Enrichment Analysis in Python
Single sample Gene Set Enrichment analysis (ssGSEA) and PTM Enrichment Analysis (PTM-SEA)
Brings bulk and pseudobulk transcriptomics to the tidyverse
MSigDB gene sets for multiple organisms in a tidy data format
Lightweight Iterative Gene set Enrichment in R
Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq
Differential expression (DE); gene set Enrichment Analysis (GSEA); single cell RNAseq studies (scRNAseq)
Enrichment Networks for Pathway Enrichment Analysis
Molecular Signatures Database (MSigDB) in a data frame
Gene Set Clustering based on Functional annotation
Julia implementation of the next generation GSEA 🏔️
Gene Set Enrichment Analysis and Over Representation Analysis analysis using R
A web-based application to perform Gene Set Enrichment Analysis (GSEA) using clusterProfiler and shiny R libraries
Interpretation of RNAseq experiments through robust, efficient comparison to public databases
Pandas API for multiple Gene Set Enrichment Analysis implementations in Python (GSEApy, cudaGSEA, GSEA)
Flexible gene set enrichment analysis
GSEA plots in ggplot2
Thermodynamically Motivated Enrichment Analysis (TMEA) is a new approach to gene set enrichment analysis.
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