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Curion, F. ; Rich-Griffin, C.* ; Agarwal, D.* ; Ouologuem, S. ; Rue-Albrecht, K.* ; May, L. ; Garcia, G.E.L.* ; Heumos, L. ; Thomas, T.* ; Lason, W.* ; Sims, D.* ; Theis, F.J. ; Dendrou, C.A.*

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

Genome Biol. 25:181 (2024)
Publ. Version/Full Text DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
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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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
ISSN (print) / ISBN 1474-760X
e-ISSN 1465-6906
Journal Genome Biology
Quellenangaben Volume: 25, Issue: 1, Pages: , Article Number: 181 Supplement: ,
Publisher BioMed Central
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Computational Biology (ICB)
Lung Health and Immunity (LHI)