Simulation, power evaluation and sample size recommendation for single-cell RNA-seq | Zendy

Keg Su | Zendy; Zhijin Wu | Zendy; Hao Wu | Zendy

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Simulation, power evaluation and sample size recommendation for single-cell RNA-seq

Author(s) -

Keg Su,

Zhijin Wu,

Hao Wu

Publication year - 2020

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btaa607

Subject(s) - sample size determination , computer science , context (archaeology) , sample (material) , statistical power , data mining , power analysis , throughput , power (physics) , statistics , algorithm , mathematics , paleontology , telecommunications , chemistry , physics , chromatography , quantum mechanics , cryptography , wireless , biology

Determining the sample size for adequate power to detect statistical significance is a crucial step at the design stage for high-throughput experiments. Even though a number of methods and tools are available for sample size calculation for microarray and RNA-seq in the context of differential expression (DE), this topic in the field of single-cell RNA sequencing is understudied. Moreover, the unique data characteristics present in scRNA-seq such as sparsity and heterogeneity increase the challenge.

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