1. Integrating single-cell genomics pipelines to discover mechanisms of stem cell differentiation
- Author
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Tessa Werner, Quan Nguyen, Stephen T. Bradford, Enakshi Sinniah, Zhixuan Wu, Sean B. Wilson, James E. Hudson, Woo Jun Shim, Joseph E. Powell, Maika Matsumoto, Nathan J. Palpant, Yuliangzi Sun, Sophie Shen, and Melissa H. Little
- Subjects
Pluripotent Stem Cells ,0303 health sciences ,Cell type ,Computer science ,Cellular differentiation ,Cell ,Cell Differentiation ,Genomics ,Computational biology ,03 medical and health sciences ,0302 clinical medicine ,medicine.anatomical_structure ,medicine ,Humans ,Molecular Medicine ,Single-Cell Analysis ,Stem cell ,Transcriptome ,Induced pluripotent stem cell ,Molecular Biology ,030217 neurology & neurosurgery ,030304 developmental biology - Abstract
Pluripotent stem cells underpin a growing sector that leverages their differentiation potential for research, industry, and clinical applications. This review evaluates the landscape of methods in single-cell transcriptomics that are enabling accelerated discovery in stem cell science. We focus on strategies for scaling stem cell differentiation through multiplexed single-cell analyses, for evaluating molecular regulation of cell differentiation using new analysis algorithms, and methods for integration and projection analysis to classify and benchmark stem cell derivatives against in vivo cell types. By discussing the available methods, comparing their strengths, and illustrating strategies for developing integrated analysis pipelines, we provide user considerations to inform their implementation and interpretation.
- Published
- 2021
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