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
Declarative creation of composable visualization for Python (Complex heatmap, Upset plot, Oncoprint and more~)
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.
Autonomous multi-agent framework to optimize scientific software
MCP server for spatial transcriptomics analysis through natural language interfaces.
pseudobulking on an AnnData object
Fast spatial deconvolution via leverage-score sketching — scales to million-spot datasets while preserving rare cell type signals.
Cell Analyzer for Flow Experiment
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