There are 1 repository under gene-sets topic.
Single sample Gene Set Enrichment analysis (ssGSEA) and PTM Enrichment Analysis (PTM-SEA)
A Snakemake workflow for performing genomic region set and gene set enrichment analyses using LOLA, GREAT, and GSEApy.
Pandas API for multiple Gene Set Enrichment Analysis implementations in Python (GSEApy, cudaGSEA, GSEA)
resVAE is a restricted latent variational autoencoder that we wrote to uncover hidden structures in gene expression data, especially using single-cell RNA sequencing. In principle it can be used with any hierarchically structured data though, so feel free to play around with it.
:chart: The package is user friendly interface based on the cgdsr and other modeling packages to explore, compare, and analyse all available Cancer Data (Clinical data, Gene Mutation, Gene Methylation, Gene Expression, Protein Phosphorylation, Copy Number Alteration) hosted by the Computational Biology Center at Memorial-Sloan-Kettering Cancer Center (MSKCC).
COVID-19 Crowd Generated Gene and Drug Set Library
R wrapper for ermineJ
A python package that consists of functions that process publicly available annotated sets of genes
Gene Set Enrichment Class Analysis for heterogeneous RNA sequencing data
Ready-to-use curated genesets for cinaR
Reference implementation of the paper Redundancy-aware unsupervised ranking based on game theory - application to gene enrichment analysis
Tools to prepare and analyze a priori molecular signatures, such as gene sets.
enabling pathway analysis of curated chip-seq data
Enables Gene Ontology (and other feature annotation) enrichment calculations and comparisons between feature sets.
Experimental version of data package associated with chipenrich
GMT files for the mulea R package
muleaData is an ExperimentHubData Bioconductor package for the mulea R package
Web application that enables users to compare the expression of genes or enrichment of gene sets between different molecular subtypes of colorectal cancer
A resource of gene expression signatures derived from the DEE2 dataset (http://dee2.io)