UCell and pyUCell: single-cell gene signature scoring for R and Python

TL;DR

UCell and pyUCell are tools for scoring gene signatures in single-cell data using R and Python, integrating with major analysis platforms.

Contribution

UCell v2 introduces a unified and efficient rank-based signature scoring framework for single-cell data in R and Python.

Findings

UCell and pyUCell provide fast and robust implementations for gene signature scoring.

They integrate with major single-cell analysis ecosystems like Seurat and scanpy.

Abstract

Gene signature scoring provides a simple yet powerful approach for quantifying biological signals within single-cell omics datasets. UCell and pyUCell offer fast and robust implementations of rank-based signature scoring for R and Python, respectively, integrating seamlessly with leading single-cell analysis ecosystems such as Seurat, Bioconductor, and scanpy/scverse.

UCell v2 is distributed as an R package by BioConductor (https://bioconductor.org/packages/UCell/) and as a Python package by pyPI (https://pypi.org/project/pyucell/).

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