Single Cell Multiomics Python Packages

scarf

Memory-efficient single-cell analysis in Python. Stream RNA, ATAC, CITE-seq and multi-omics from local or remote Zarr stores, from laptop to atlas scale, with reusable fingerprinted results.

cytome

Single-file format for single-cell multi-omics and spatial transcriptomics — matrices, metadata, embeddings, fragments and provenance in one SQLite-backed .cytome file, with SQL metadata queries and genomic range indexes.

scglue

Graph-linked unified embedding for single-cell multi-omics data integration

cosg

Accurate and fast cell marker gene identification with COSG

cytearc

Fast, out-of-core single-cell analysis in Python for RNA, ATAC, protein, and multi-omic data, scaling to 100M+ cells. Mount remote datasets, work within a memory budget, and trace every result through built-in provenance.

scmidas

PyTorch implementation of the MIDAS algorithm for single-cell multimodal data integration (Nature Biotechnology 2024).

airqtl

Single-cell eQTL mapping and causal gene regulatory network inference at high efficiency and accuracy

scoit

SCOIT is an implementation of a probabilistic tensor decomposition framework for single-cell multi-omics data integration.

dictys

Context specific and dynamic gene regulatory network reconstruction and analysis

matchclot

Python package implementing our method MatchCLOT for multimodal single-cell data integration