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Performance Assessment and Selection of Normalization Procedures for Single-Cell RNA-Seq.

ABSTRACT: Systematic measurement biases make normalization an essential step in single-cell RNA sequencing (scRNA-seq) analysis. There may be multiple competing considerations behind the assessment of normalization performance, of which some may be study specific. We have developed "scone"- a flexible framework for assessing performance based on a comprehensive panel of data-driven metrics. Through graphical summaries and quantitative reports, scone summarizes trade-offs and ranks large numbers of normalization methods by panel performance. The method is implemented in the open-source Bioconductor R software package scone. We show that top-performing normalization methods lead to better agreement with independent validation data for a collection of scRNA-seq datasets. scone can be downloaded at http://bioconductor.org/packages/scone/.

SUBMITTER: Cole MB

PROVIDER: S-EPMC6544759 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Performance Assessment and Selection of Normalization Procedures for Single-Cell RNA-Seq.

Cole Michael B MB Risso Davide D Wagner Allon A DeTomaso David D Ngai John J Purdom Elizabeth E Dudoit Sandrine S Yosef Nir N

Cell systems 20190401 4

Systematic measurement biases make normalization an essential step in single-cell RNA sequencing (scRNA-seq) analysis. There may be multiple competing considerations behind the assessment of normalization performance, of which some may be study specific. We have developed "scone"- a flexible framework for assessing performance based on a comprehensive panel of data-driven metrics. Through graphical summaries and quantitative reports, scone summarizes trade-offs and ranks large numbers of normali ...[more]

PMID: 31022373

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