A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.201505002>, Stuart T, Butler A, et al (2019) <doi:10.1016/j.cell.2019年05月03日1>, and Hao, Hao, et al (2020) <doi:10.1101/2020.10.12.335331> for more details.
Author:
Andrew Butler
ORCID iD
[ctb],
Saket Choudhary
ORCID iD
[ctb],
David Collins
ORCID iD
[ctb],
Charlotte Darby
ORCID iD
[ctb],
Jeff Farrell [ctb],
Isabella Grabski
ORCID iD
[ctb],
Christoph Hafemeister
ORCID iD [ctb],
Yuhan Hao
ORCID iD [ctb],
Austin Hartman
ORCID iD
[ctb],
Paul Hoffman
ORCID iD
[ctb],
Jaison Jain
ORCID iD [ctb],
Longda Jiang
ORCID iD
[ctb],
Madeline Kowalski
ORCID iD
[ctb],
Skylar Li [ctb],
Gesmira Molla
ORCID iD
[ctb],
Efthymia Papalexi
ORCID iD
[ctb],
Patrick Roelli [ctb],
Rahul Satija
ORCID iD
[aut, cre],
Karthik Shekhar [ctb],
Anagha Shenoy
ORCID iD
[ctb],
Avi Srivastava
ORCID iD
[ctb],
Tim Stuart
ORCID iD [ctb],
Kristof Torkenczy
ORCID iD
[ctb],
Brian Zhang [ctb],
Shiwei Zheng
ORCID iD
[ctb],
Satija Lab and Collaborators [fnd]