Searching across hundreds of databases

Our searching services are busy right now. Your search will reload in five seconds.

Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

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

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:∼jiezhou/replication/. The expression data is deposited in the Gene Expression Omnibus under the accession ID GSE51403.

Pubmed ID: 24319002 RIS Download

Mesh terms: Gene Expression Profiling | High-Throughput Nucleotide Sequencing | Humans | MCF-7 Cells | Reproducibility of Results | Sample Size | Sequence Analysis, RNA