GEO series

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

GSE51403 Homo sapiens Expression profiling by high throughput sequencing 14 samples Submitted 2014/01/07 Platform GPL11154

Summary

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 MCF-7, adding more sequencing depth after 10M reads gives diminishing returns on power to detect DE genes, while 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 perform 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

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Direct links to NCBI, no account and no request form: the whole study as GSE51403_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 14 samples. Raw sequencing reads are also available from ENA.

Whole study · RAW.tar ↓ Series matrix ↓ All supplementary files ↗ Raw reads on ENA ↗

Also filed as BioProject PRJNA222975 and SRA study SRP031476. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 24319002) ↗

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