Original language | English |
---|---|
Pages (from-to) | 163-166 |
Number of pages | 4 |
Journal | Nature Biotechnology |
Volume | 40 |
Issue number | 2 |
DOIs | |
State | Published - Feb 2022 |
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In: Nature Biotechnology, Vol. 40, No. 2, 02.2022, p. 163-166.
Research output: Contribution to journal › Letter › peer-review
TY - JOUR
T1 - A Python library for probabilistic analysis of single-cell omics data
AU - Gayoso, Adam
AU - Lopez, Romain
AU - Xing, Galen
AU - Boyeau, Pierre
AU - Valiollah Pour Amiri, Valeh
AU - Hong, Justin
AU - Wu, Katherine
AU - Jayasuriya, Michael
AU - Mehlman, Edouard
AU - Langevin, Maxime
AU - Liu, Yining
AU - Samaran, Jules
AU - Misrachi, Gabriel
AU - Nazaret, Achille
AU - Clivio, Oscar
AU - Xu, Chenling
AU - Ashuach, Tal
AU - Gabitto, Mariano
AU - Lotfollahi, Mohammad
AU - Svensson, Valentine
AU - da Veiga Beltrame, Eduardo
AU - Kleshchevnikov, Vitalii
AU - Talavera-López, Carlos
AU - Pachter, Lior
AU - Theis, Fabian J.
AU - Streets, Aaron
AU - Jordan, Michael I.
AU - Regier, Jeffrey
AU - Yosef, Nir
N1 - Funding Information: We acknowledge members of the Streets and Yosef laboratories for general feedback. We thank all the GitHub users who contributed code to scvi-tools over the years. We thank Nicholas Everetts for help with the analysis of the Drosophila data. We thank David Kelley and Nick Bernstein for help implementing Solo. We thank Marco Wagenstetter and Sergei Rybakov for help with the transition of the scGen package to use scvi-tools, as well as feedback on the scArches implementation. We thank Hector Roux de Bézieux for insightful discussions about the R ecosystem. We thank Kieran Campbell and Allen Zhang for clarifying aspects of the original CellAssign implementation. We thank the Pyro team, including Eli Bingham, Martin Jankowiak and Fritz Obermeyer, for help integrating Pyro in scvi-tools. Research reported in this manuscript was supported by the NIGMS of the National Institutes of Health under award number R35GM124916 and by the Chan-Zuckerberg Foundation Network under grant number 2019-02452. O.C. is supported by the EPSRC Centre for Doctoral Training in Modern Statistics and Statistical Machine Learning (EP/S023151/1, studentship 2420649). A.G. is supported by NIH Training Grant 5T32HG000047-19. A.S. and N.Y. are Chan Zuckerberg Biohub investigators. Funding Information: We acknowledge members of the Streets and Yosef laboratories for general feedback. We thank all the GitHub users who contributed code to scvi-tools over the years. We thank Nicholas Everetts for help with the analysis of the Drosophila data. We thank David Kelley and Nick Bernstein for help implementing Solo. We thank Marco Wagenstetter and Sergei Rybakov for help with the transition of the scGen package to use scvi-tools, as well as feedback on the scArches implementation. We thank Hector Roux de Bézieux for insightful discussions about the R ecosystem. We thank Kieran Campbell and Allen Zhang for clarifying aspects of the original CellAssign implementation. We thank the Pyro team, including Eli Bingham, Martin Jankowiak and Fritz Obermeyer, for help integrating Pyro in scvi-tools. Research reported in this manuscript was supported by the NIGMS of the National Institutes of Health under award number R35GM124916 and by the Chan-Zuckerberg Foundation Network under grant number 2019-02452. O.C. is supported by the EPSRC Centre for Doctoral Training in Modern Statistics and Statistical Machine Learning (EP/S023151/1, studentship 2420649). A.G. is supported by NIH Training Grant 5T32HG000047-19. A.S. and N.Y. are Chan Zuckerberg Biohub investigators.
PY - 2022/2
Y1 - 2022/2
UR - http://www.scopus.com/inward/record.url?scp=85124370073&partnerID=8YFLogxK
U2 - 10.1038/s41587-021-01206-w
DO - 10.1038/s41587-021-01206-w
M3 - Letter
C2 - 35132262
AN - SCOPUS:85124370073
SN - 1087-0156
VL - 40
SP - 163
EP - 166
JO - Nature Biotechnology
JF - Nature Biotechnology
IS - 2
ER -