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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)
Verlagsversion 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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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
ISSN (print) / ISBN 1474-760X
e-ISSN 1465-6906
Zeitschrift Genome Biology
Quellenangaben Band: 25, Heft: 1, Seiten: , Artikelnummer: 181 Supplement: ,
Verlag BioMed Central
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)
Lung Health and Immunity (LHI)