Reverse Dependencies of gseapy

The following projects have a declared dependency on gseapy:

• acore — A Python package with statistical functions to analyse multimodal molecular data
• bengrn — benchmarking gene regulatory networks
• besca — Collection of BEDA internal python functions for analysing single cell RNAseq data.
• bionetcomp — BioNetComp: A Python package for biological network comparison from STRING database.
• biosofa — Probabilistic factor analysis model with covariate guided factors
• Broad-GenePy — A useful module for any CompBio
• burstlink — A user-friendly package for analyzing gene interactions and transcriptional bursting.
• cansig — Discovering de novo shared transcriptional programs in single cancer cells
• cell2cell — TBD
• CellGen — CellGen: a computational model for predicting the cellular response to diverse perturbation
• clep — A Hybrid Data and Knowledge Driven Framework for Generating Patient Representations
• concord-sc — CONCORD: Contrastive Learning for Cross-domain Reconciliation and Discovery
• cospar — A toolkit for dynamic inference of cell fate by integrating state and lineage information.
• dpks — Data processing package for the analysis of omics data
• dynamo-release — Mapping Vector Field of Single Cells
• esmecata — EsMeCaTa: Estimating Metabolic Capabilties from Taxonomy
• exoTras — exosome-containing droplet identification and source tracking in scRNA-seq data
• genes2genes — A tool for aligning gene expression trajectories of single-cell reference and query systems
• genetk — for enrichment and network analysis given gene list
• grape-pi — Using graph neural networks to enhance protein identification using protein interaction networks.
• graphpack — A Python tool to perform graph compression and visualization
• grnndata — Awesome gene regulatory network enhanced anndata
• gseagui — GUI tools for gene set enrichment analysis
• JKBio — A useful module for any CompBio
• kailin — KAILINss - TOGGLE(KAILIN): Single Cell Fate Tracing tools
• LittleSnowFox — KAILINss - TOGGLE(KAILIN): Single Cell Fate Tracing tools
• metachat — Spatial metabolic communication flow of single cells.
• methyltree — High-resolution, noninvasive single-cell lineage tracing based on DNA methylation epimutations.
• mmcci — A Python package for processing multi-platform, multi-sample CCI data
• MultiGATE — MultiGATE single cell
• nico-sc-sp — This package finds covariation patterns between interacted niche cell types from single-cell resolution spatial transcriptomics data.
• omicscope — OmicScope: from quantitative proteomics to systems biology.
• PanClassif — A method to improve TCGA pancancer classifiers performance
• pegasuspy — Pegasus is a Python package for analyzing sc/snRNA-seq data of millions of cells
• popari — Popari: a probabilistic graphical model for integrated spatial transcriptomics analysis
• proteomics-downstream-analysis — A package for downstream data analysis of proteomics data
• pygenricher — no summary
• Pyomic — A python framework library for omics analysis
• ReadyCellOne — Computational tools to enable task-centric cell engineering
• sc-var — An approch for interpreting disease-associated human variants using single-cell epigenomics
• scatrex — Map single-cell transcriptomes to copy number evolutionary trees.
• scLift — SCIV: Unveiling the pivotal cell types involved in variant function regulation at a single-cell resolution
• scprint — scPRINT is a Large Cell Model for Gene Network Inference, Denoising and more from scRNAseq data
• scTM — A toolbox for single cell topic models
• scToolsGW — convenience wrappers around common scanpy functions and workflows
• sctriangulate — A Python package to mix-and-match conflicting clustering results in single cell analysis, and generate reconciled clustering solutions.
• sequana — A set of standalone application and pipelines dedicated to NGS analysis
• SEVtras — sEV-containing droplet identification in scRNA-seq data
• SIMPApy — Normalized Single Sample Integrated Multiomics Pathway Analysis
• siVAE — scalable and interpretable Variational Autoencoder
• SpaGFT — SpaGFT is a python package to analyze spatial transcriptomcs data
• spider-st — Identifying spatially variable interactions
• spiderYa — Identifying spatially variable interactions
• tapir-rna — Transcriptional Analysis in Python Imported from R
• TiRank — A comprehensive analysis tool for transfering phenotype of bulk transcritomic data to single cell or spatial transcriptomic data.
• TMEImmune — Python package for calculating TME scores
• topicpy — Package to extract information from topic models.