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

Annotated data.

An end-to-end Single-Cell Pipeline designed to facilitate comprehensive analysis and exploration of single-cell data.

Cell type annotation for single-cell RNA-seq using multi-LLM consensus

scplotter is an R package that is built upon plotthis. It provides a set of functions to visualize single-cell sequencing and spatial data in an easy and efficient way.

muon is a multimodal omics Python framework

Enables cellxgene to generate violin, stacked violin, stacked bar, heatmap, volcano, embedding, dot, track, density, 2D density, sankey and dual-gene plot in high-resolution SVG/PNG format. It also performs differential gene expression analysis and provides a Command Line Interface (CLI) for advanced users to perform analysis using python and R.

Cell type annotation with local Large Language Models (LLMs) - Ensuring privacy and speed with extensive customized reports

Convert between AnnData and SingleCellExperiment

Multi-agent LLM driven cell type annotation for single-cell RNA-Seq data

Learning cell communication from spatial graphs of cells

Bring your single-cell data to life

BANKSY: Spatial Clustering Algorithm that Unifies Cell-Typing and Tissue Domain Segmentation. Python package for spatial transcriptomics analysis.

pseudobulking on an AnnData object

MCP server for spatial transcriptomics analysis through natural language interfaces.

Translates an AnnData object with mouse gene symbols into one with human gene symbols by mapping orthologs from biomart.

Fast spatial deconvolution via leverage-score sketching — scales to million-spot datasets while preserving rare cell type signals.

Brain-Referenced In vivo-to-in vitro Developmental Guidance and Evaluation.

This repository extends scanpy to handle flow and mass cytometry data.

Single-cell temporal analysis of neutrophils using DRVI