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

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.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1186/s13059-024-03322-7

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Institution:
University of Oxford
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Author
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Institution:
University of Oxford
Role:
Author
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Institution:
University of Oxford
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Funder identifier:
https://ror.org/018mejw64
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Funder identifier:
https://ror.org/029chgv08
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Funder identifier:
https://ror.org/04e3zg361
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Funder identifier:
https://ror.org/03x94j517


Publisher:
BioMed Central
Journal:
Genome Biology More from this journal
Volume:
25
Issue:
1
Article number:
181
Publication date:
2024-07-08
Acceptance date:
2024-06-25
DOI:
EISSN:
1474-760X


Language:
English
Source identifiers:
2095716
Deposit date:
2024-07-08

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