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

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 syste...

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Published in:Genome Biology Vol. 25; no. 1; p. 181
Main Authors: Curion, Fabiola, Rich-Griffin, Charlotte, Agarwal, Devika, Ouologuem, Sarah, Rue-Albrecht, Kevin, May, Lilly, Garcia, Giulia E. L., Heumos, Lukas, Thomas, Tom, Lason, Wojciech, Sims, David, Theis, Fabian J., Dendrou, Calliope A.
Format: Journal Article
Language:English
Published: London BioMed Central 08.07.2024
Springer Nature B.V
BMC
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ISSN:1474-760X, 1474-7596, 1474-760X
Online Access:Get full text
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Summary: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.
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ISSN:1474-760X
1474-7596
1474-760X
DOI:10.1186/s13059-024-03322-7