Scone – performance assessment and selection of normalization procedures for single-cell RNA-Seq

rna-seq

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. Researchers at UC Berkeley 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. The developers show that top-performing normalization methods lead to better agreement with independent validation data for a collection of scRNA-seq datasets.

Availability – scone can be downloaded at http://bioconductor.org/packages/scone/.

Cole MB, Risso D, Wagner A, DeTomaso D, Ngai J, Purdom E, Dudoit S, Yosef N. (2019) Performance Assessment and Selection of Normalization Procedures for Single-Cell RNA-Seq. Cell Syst 8(4):315-328.e8. [abstract]

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