📊 A universal enrichment tool for interpreting omics data
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Updated
Nov 29, 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
Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq
Lightweight Iterative Gene set Enrichment in R
Enrichment Networks for Pathway Enrichment Analysis
Differential expression (DE); gene set Enrichment Analysis (GSEA); single cell RNAseq studies (scRNAseq)
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)
Comprehensive Single-Cell Annotation and Transcriptomic Analysis Toolkit
Flexible gene set enrichment analysis
Function Enrichment analysis and Network construction
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