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

Abstract Motivation The detection of distinct cellular identities is central to the analysis of single-cell RNA sequencing (scRNA-seq) experiments. However, in perturbation experiments, current methods typically fail to correctly match cell states between conditions or erroneously remove population...

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Veröffentlicht in:	Bioinformatics (Oxford, England) England), 2023-05, Vol.39 (5)
Hauptverfasser:	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, William Evan, Bradham, Cynthia A
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Cluster Analysis Gene Expression Profiling - methods Original Paper Sequence Analysis, RNA - methods Single-Cell Analysis - methods Transcriptome
Online-Zugang:	Volltext
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