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RNA-seq differential expression studies: more sequence or more replication?

, , and . Bioinformatics 30 (3): 301-304 (February 2014)

Abstract

RNA-seq is replacing microarrays as the primary tool for gene expression studies. Many RNA-seq studies have used insufficient biological replicates, resulting in low statistical power and inefficient use of sequencing resources.We show the explicit trade-off between more biological replicates and deeper sequencing in increasing power to detect differentially expressed (DE) genes. In the human cell line MCF7, adding more sequencing depth after 10 M reads gives diminishing returns on power to detect DE genes, whereas adding biological replicates improves power significantly regardless of sequencing depth. We also propose a cost-effectiveness metric for guiding the design of large-scale RNA-seq DE studies. Our analysis showed that sequencing less reads and performing more biological replication is an effective strategy to increase power and accuracy in large-scale differential expression RNA-seq studies, and provided new insights into efficient experiment design of RNA-seq studies.The code used in this paper is provided on: http://home.uchicago.edu/∼jiezhou/replication/. The expression data is deposited in the Gene Expression Omnibus under the accession ID GSE51403.

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RNA-seq differential expression studies: more sequence or more replication? - PubMed - NCBI

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Liu:2014:Bioinformatics:24319002
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