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Bioinformatics. 2014 Feb 1;30(3):301-4. doi: 10.1093/bioinformatics/btt688. Epub 2013 Dec 6.

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

Author information

1
Institute of Genomics and Systems Biology, Committee on Development, Regeneration, and Stem Cell Biology and Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA.

Abstract

MOTIVATION:

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.

RESULTS:

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.

AVAILABILITY AND IMPLEMENTATION:

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.

PMID:
24319002
PMCID:
PMC3904521
DOI:
10.1093/bioinformatics/btt688
[Indexed for MEDLINE]
Free PMC Article

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