Single-cell analysis in Python. Scales to >1M cells.

An interactive explorer for single-cell transcriptomics data

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

Annotated data.

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.

Fusing Histology and Genomics via Deep Learning - IEEE TMI

Single cell perturbation prediction

The COnstraint-Based Reconstruction and Analysis Toolbox. Documentation:

starfish: unified pipelines for image-based transcriptomics

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

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

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

Differential expression analysis for single-cell RNA-seq data.

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

R package for analyzing single-cell RNA-seq data

A list of web-based interactive biological data visualizations.

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

Brings bulk and pseudobulk transcriptomics to the tidyverse

Python package to perform enrichment analysis from omics data.

Transcript discovery and quantification with long RNA reads (Nanopores and PacBio)