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Quality Control of Single-Cell RNA-seq

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Computational Methods for Single-Cell Data Analysis

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1935))

Abstract

Single-cell RNA-seq (scRNA-seq) is emerging as a promising technology to characterize and dissect the cell-to-cell variability. However, the mixture of technical noise and intrinsic biological variability makes separating technical artifacts from real biological variation cells particularly challenging. Proper detection and filtering out technical artifacts before downstream analysis are critical. Here, we present a protocol that integrates both gene expression patterns and data quality to detect technical artifacts in scRNA-seq samples.

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Author information

Authors and Affiliations

  1. Regenerative Biology Laboratory, Morgridge Institute for Research, Madison, WI, USA

    Peng Jiang

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  1. Peng Jiang
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Corresponding author

Correspondence to Peng Jiang .

Editor information

Editors and Affiliations

  1. Dana–Farber Cancer Institute and Harvard Chan, School of Public Health, Boston, MA, USA

    Guo-Cheng Yuan

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Jiang, P. (2019). Quality Control of Single-Cell RNA-seq. In: Yuan, GC. (eds) Computational Methods for Single-Cell Data Analysis. Methods in Molecular Biology, vol 1935. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-9057-3_1

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  • DOI: https://doi.org/10.1007/978-1-4939-9057-3_1

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-9056-6

  • Online ISBN: 978-1-4939-9057-3

  • eBook Packages: Springer Protocols

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