Investigating Inter- and Intrasample Diversity of Single-Cell RNA Sequencing Datasets.

Abstract:

Tumor heterogeneity can arise from a variety of extrinsic and intrinsic sources and drives unfavorable outcomes. With recent technological advances, single-cell RNA sequencing has become a way for researchers to easily assay tumor heterogeneity at the transcriptomic level with high resolution. However, ongoing research focuses on different ways to analyze this big data and how to compare across multiple different samples. In this chapter, we provide a practical guide to calculate inter- and intrasample diversity metrics from single-cell RNA sequencing datasets. These measures of diversity are adapted from commonly used metrics in statistics and ecology to quantify and compare sample heterogeneity at single-cell resolution.

Profile Page: http://compmodelmatch.org/publications/11

PubMed ID: 32926367

Meetings: Finding Your Inner Modeler IV

Publication type: InBook

Journal: Methods Mol Biol

Citation: Methods Mol Biol. 2021;2194:177-186. doi: 10.1007/978-1-0716-0849-4_10.

Date Published: 14th Sep 2020

Registered Mode: by PubMed ID

Authors: M. C. Ferrall-Fairbanks, P. M. Altrock

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Created: 5th Aug 2021 at 17:44

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