Panpipes: a pipeline for multiomic single-cell and spatial transcriptomic data analysis

Fabiola Curion, Charlotte Rich-Griffin, Devika Agarwal, Sarah Ouologuem, Kevin Rue-Albrecht, Lilly May, Giulia E.L. Garcia, Lukas Heumos, Tom Thomas, Wojciech Lason, David Sims, Fabian J. Theis, Calliope A. Dendrou

Research output: Contribution to journalArticlepeer-review

Abstract

Single-cell multiomic analysis of the epigenome, transcriptome, and proteome allows for comprehensive characterization of the molecular circuitry that underpins cell identity and state. However, the holistic interpretation of such datasets presents a challenge given a paucity of approaches for systematic, joint evaluation of different modalities. Here, we present Panpipes, a set of computational workflows designed to automate multimodal single-cell and spatial transcriptomic analyses by incorporating widely-used Python-based tools to perform quality control, preprocessing, integration, clustering, and reference mapping at scale. Panpipes allows reliable and customizable analysis and evaluation of individual and integrated modalities, thereby empowering decision-making before downstream investigations.

Original languageEnglish
Article number181
JournalGenome Biology
Volume25
Issue number1
DOIs
StatePublished - Dec 2024

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