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Heumos, L. ; Ji, Y. ; May, L. ; Green, T.D.* ; Peidli, S.* ; Zhang, X. ; Wu, X. ; Ostner, J. ; Schumacher, A. ; Hrovatin, K. ; Müller, M. ; Chong, F. ; Sturm, G.* ; Tejada Lapuerta, A. ; Dann, E.* ; Dong, M.* ; Pinto, G. ; Bahrami, M. ; Gold, I. ; Rybakov, S. ; Namsaraeva, A. ; Moinfar, A.A. ; Zheng, Z. ; Roellin, E. ; Mekki, I.I ; Sander, C.* ; Lotfollahi, M. ; Schiller, H.B. ; Theis, F.J.

Pertpy: An end-to-end framework for perturbation analysis.

Nat. Methods, 30 (2025)
Verlagsversion Forschungsdaten DOI PMC
Open Access Hybrid
Creative Commons Lizenzvertrag
Advances in single-cell technology have enabled the measurement of cell-resolved molecular states across a variety of cell lines and tissues under a plethora of genetic, chemical, environmental or disease perturbations. Current methods focus on differential comparison or are specific to a particular task in a multi-condition setting with purely statistical perspectives. The quickly growing number, size and complexity of such studies require a scalable analysis framework that takes existing biological context into account. Here we present pertpy, a Python-based modular framework for the analysis of large-scale single-cell perturbation experiments. Pertpy provides access to harmonized perturbation datasets and metadata databases along with numerous fast and user-friendly implementations of both established and novel methods, such as automatic metadata annotation or perturbation distances, to efficiently analyze perturbation data. As part of the scverse ecosystem, pertpy interoperates with existing single-cell analysis libraries and is designed to be easily extended.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Metadata ; Perturbation (astronomy) ; Modular Design ; Implementation ; Scalability ; Annotation; Cell; Melanoma; Platform
ISSN (print) / ISBN 1548-7091
e-ISSN 1548-7105
Zeitschrift Nature Methods
Quellenangaben Band: , Heft: , Seiten: 30 Artikelnummer: , Supplement: ,
Verlag Nature Publishing Group
Verlagsort New York, NY
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)
Helmholtz Pioneer Campus (HPC)
Helmholtz Artifical Intelligence Cooperation Unit (HAICU)
Research Unit Precision Regenerative Medicine (PRM)
Förderungen KH acknowledges financial support from Joachim Herz Stiftung via Add-on Fellowships for Interdisciplinary Life Science and support from Helmholtz Association under the joint research school 'Munich School for Data Science'.
MB is supported by the Helmholtz Association under the joint research school 'Munich School For Data Science'
Wellcome-LEAP Delta Tissue
AN is supported by the Konrad Zuse School of Excellence in Learning and Intelligent Systems (ELIZA) through the DAAD programme Konrad Zuse Schools of Excellence in Artificial Intelligence, sponsored by the Federal Ministry of Education and Research.
Supported by the Helmholtz Association under the joint research school 'Munich School For Data Science'
Open Targets (OTAR-3083)