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Nat Methods. 2017 Oct;14(10):967-970. doi: 10.1038/nmeth.4427. Epub 2017 Sep 4.

Sampling strategies to capture single-cell heterogeneity.

Author information

1
Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California, USA.
2
Department of Medicine, University of California, San Francisco, San Francisco, California, USA.
3
Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California, USA.
4
Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
5
Department of Pathology, University of Arizona, Tucson, Arizona, USA.
6
Department of Pathology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
7
Department of Surgery, University of California, San Francisco, San Francisco, California, USA.

Abstract

Advances in single-cell technologies have highlighted the prevalence and biological significance of cellular heterogeneity. A critical question researchers face is how to design experiments that faithfully capture the true range of heterogeneity from samples of cellular populations. Here we develop a data-driven approach, illustrated in the context of image data, that estimates the sampling depth required for prospective investigations of single-cell heterogeneity from an existing collection of samples.

PMID:
28869755
PMCID:
PMC5658002
DOI:
10.1038/nmeth.4427
[Indexed for MEDLINE]
Free PMC Article

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