Single-cell analysis in Python. Scales to >100M cells.

🧬 gget enables efficient querying of genomic reference databases

Foundation Models for Genomics & Transcriptomics

An interactive explorer for single-cell transcriptomics data

Annotated data.

A Python implementation of the DESeq2 pipeline for bulk RNA-seq DEA.

pySCENIC is a lightning-fast python implementation of the SCENIC pipeline (Single-Cell rEgulatory Network Inference and Clustering) which enables biologists to infer transcription factors, gene regulatory networks and cell types from single-cell RNA-seq data.

Single cell perturbation prediction

Fusing Histology and Genomics via Deep Learning - IEEE TMI

Python package to perform enrichment analysis from omics data.

The COnstraint-Based Reconstruction and Analysis Toolbox. Documentation:

R package for analyzing and interactively exploring large-scale single-cell RNA-seq datasets

Reference-guided transcript discovery and quantification for long read RNA-Seq data

starfish: unified pipelines for image-based transcriptomics

Automatic Annotation on Cell Types of Clusters from Single-Cell RNA Sequencing Data

A list of web-based interactive biological data visualizations.

A universal toolkit for upstream processing of long RNA reads

R/shiny interface for interactive visualization of data in SummarizedExperiment objects

🐟 🔬🦀 alevin-fry is an efficient and flexible tool for processing single-cell sequencing data, currently focused on single-cell transcriptomics and feature barcoding.

An ontology of cell types