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

doi:10.1186/s13059-024-03322-7

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

Genome Biol. 2024 Jul 8;25(1):181. doi: 10.1186/s13059-024-03322-7.

Authors

Fabiola Curion^#^{1

2}, Charlotte Rich-Griffin^#³, Devika Agarwal^{3

4}, Sarah Ouologuem¹, Kevin Rue-Albrecht⁵, Lilly May¹, Giulia E L Garcia^{4

6}, Lukas Heumos^{1

7

8}, Tom Thomas^{3

4

9}, Wojciech Lason¹⁰, David Sims⁵, Fabian J Theis^{11

12

13}, Calliope A Dendrou^{14

15

16}

Affiliations

¹ Department of Computational Health, Institute of Computational Biology, Helmholtz Munich, Germany.
² Department of Mathematics, School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.
³ Nuffield Department of Medicine, Centre for Human Genetics, University of Oxford, Oxford, UK.
⁴ Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK.
⁵ MRC WIMM Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK.
⁶ Doctoral Training Centre, University of Oxford, Oxford, UK.
⁷ Comprehensive Pneumology Center With the CPC-M bioArchive, Helmholtz Zentrum Munich, Member of the German Center for Lung Research (DZL), Munich, Germany.
⁸ TUM School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany.
⁹ Nuffield Department of Medicine, Translational Gastroenterology Unit, University of Oxford, Oxford, UK.
¹⁰ Nuffield Department of Medicine, Respiratory Medicine Unit, Experimental Medicine Division, University of Oxford, John Radcliffe Hospital, Oxford, UK.
¹¹ Department of Computational Health, Institute of Computational Biology, Helmholtz Munich, Germany. [email protected].
¹² Department of Mathematics, School of Computation, Information and Technology, Technical University of Munich, Munich, Germany. [email protected].
¹³ TUM School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany. [email protected].
¹⁴ Nuffield Department of Medicine, Centre for Human Genetics, University of Oxford, Oxford, UK. [email protected].
¹⁵ Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK. [email protected].
¹⁶ NIHR Oxford Biomedical Research Centre, Oxford, UK. [email protected].

^# Contributed equally.

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.

MeSH terms

Gene Expression Profiling / methods
Humans
Single-Cell Analysis* / methods
Software*
Transcriptome*
Workflow

Abstract

MeSH terms

Grants and funding