Normalization for Single-Cell RNA-Seq Data Analysis

Rhonda Bacher

doi:10.1007/978-1-4939-9057-3_2

Normalization for Single-Cell RNA-Seq Data Analysis

Methods Mol Biol. 2019:1935:11-23. doi: 10.1007/978-1-4939-9057-3_2.

Author

Rhonda Bacher¹

Affiliation

¹ Department of Biostatistics, University of Florida, Gainesville, FL, USA. [email protected].

PMID: 30758817
DOI: 10.1007/978-1-4939-9057-3_2

Abstract

In this chapter, we describe a robust normalization method for single-cell RNA sequencing data. The procedure, SCnorm, is implemented in R and is part of Bioconductor. Also included in the package are diagnostic functions to visualize normalization performance. This chapter provides an overview of the methodology and provides example work-flows.

Keywords: Gene expression; High-throughput sequencing; Normalization; Read count; Single-cell RNA-seq.

Publication types

Review

MeSH terms

Animals
Data Analysis
Gene Expression Profiling / methods
High-Throughput Nucleotide Sequencing / methods*
RNA / genetics*
Sequence Analysis, RNA / methods*
Single-Cell Analysis / methods*

Substances

RNA