Anndata Python Packages

anndata

Annotated data.

scanpy

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

mudata

Multimodal Data (.h5mu) implementation for Python

annsel

A user-friendly library that brings familiar DataFrame-style operations to AnnData objects with a simple and expressive API.

muon

muon is a multimodal omics Python framework

rapids-singlecell

rapids-singlecell: GPU-accelerated framework for scRNA analysis

pertpy

Single-cell perturbation analysis

ambidose

AmbiDose is a conservative, cell-aware Python toolkit for ambient RNA correction in droplet scRNA-seq. It estimates sample-specific ambient profiles and per-cell doses, protects native cell-type signals, preserves sparsity, and never inflates counts.

adpbulk

pseudobulking on an AnnData object

cirrocumulus

Bring your single-cell data to life

annsql

The AnnSQL package enables SQL based queries on AnnData objects.

metalcyte

Fast single-cell RNA-seq analysis on Apple silicon Macs, with a Rust engine, Metal GPU kernels and support for datasets larger than memory

pylimma

Python port of R limma for differential expression analysis

cytetype

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

bonesistools

Python toolkit from omics data to executable models

alphapepttools

Search- and quantification-engine agnostic biological interpretation of proteomics data

rapids-singlecell-cu12

rapids-singlecell: GPU-accelerated framework for scRNA analysis

pyadata-cli

A CLI for operations with AnnData objects in .h5ad and .zarr files

scxpand

scXpand: detection of T-cell clonal expansion from single-cell RNA sequencing

rapids-singlecell-cu13

rapids-singlecell: GPU-accelerated framework for scRNA analysis

pytximport

Feature-rich Python implementation of the tximport package for gene count estimation.

scxpand-cuda

scXpand: detection of T-cell clonal expansion from single-cell RNA sequencing

drvi-py

Unsupervised Deep Disentangled Representation of Single-Cell Omics

clonetrast

CloneTrast reveals pan-cancer clonal niches of T-cells from single-cell RNA sequencing using contrastive learning