ICAT: a novel algorithm to robustly identify cell states following perturbations in single cell transcriptomes

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This version posted December 23, 2022. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a Creative Commons license Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Date Issued
2022-05-29
Publisher Version
10.1101/2022.05.26.493603
Author(s)
Hawkins, Dakota Y.
Zuch, Daniel T.
Huth, James
Rodriguez-Sastre, Nahomie
McCutcheon, Kelley R.
Glick, Abigail
Lion, Alexandra T.
Thomas, Christopher F.
Descoteaux, Abigail E.
Johnson, W. Evan
Bradham, Cynthia A.
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Permanent Link
https://hdl.handle.net/2144/46591
Version
First author draft
Citation (published version)
D.Y. Hawkins, D.T. Zuch, J. Huth, N. Rodriguez-Sastre, K.R. McCutcheon, A. Glick, A.T. Lion, C.F. Thomas, A.E. Descoteaux, W.E. Johnson, C.A. Bradham. 2022. "ICAT: A Novel Algorithm to Robustly Identify Cell States Following Perturbations in Single Cell Transcriptomes" https://doi.org/10.1101/2022.05.26.493603
Rights
This version posted December 23, 2022. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a Creative Commons license Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
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