A Python library for probabilistic analysis of single-cell omics data

Gayoso A, Lopez R, Xing G, Boyeau P, Amiri VVP, Hong J, Wu K, Jayasuriya M, Mehlman E, Langevin M, Liu Y, Samaran J, Misrachi G, Nazaret A, Clivio O, Xu C, Ashuach T, Gabitto M, Lotfollahi M, Svensson V, Beltrame EDV, Kleshchevnikov V, Talavera-Lopez C, Pachter L, Theis FJ, Streets A, Jordan MI, Regier J, Yosef N (2022)

Publication Type: Journal article

Publication year: 2022

Journal

Nature Biotechnology Nature Publishing Group

Book Volume: 40

Pages Range: 163-166

Journal Issue: 2

DOI: 10.1038/s41587-021-01206-w

Involved external institutions

University of California, Berkeley

United States (USA) (US) École Normale Supérieure Paris-Saclay / ENS Cachan

France (FR) École Polytechnique - Université Paris-Saclay

France (FR) Columbia University

United States (USA) (US) PSL Research University / Université de recherche Paris Sciences et Lettres

France (FR) Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (HMGU) / Helmholtz Munich

Germany (DE) Serqet Therapeutics

United States (USA) (US) California Institute of Technology (Caltech)

United States (USA) (US) Wellcome Trust Sanger Institute - Genome Research Limited

United Kingdom (GB) Chan Zuckerberg Biohub / CZ Biohup

United States (USA) (US) University of Michigan

United States (USA) (US)

How to cite

APA:

Gayoso, A., Lopez, R., Xing, G., Boyeau, P., Amiri, V.V.P., Hong, J.,... Yosef, N. (2022). A Python library for probabilistic analysis of single-cell omics data. Nature Biotechnology, 40(2), 163-166. https://doi.org/10.1038/s41587-021-01206-w

MLA:

Gayoso, Adam, et al. "A Python library for probabilistic analysis of single-cell omics data." Nature Biotechnology 40.2 (2022): 163-166.

BibTeX: Download