期刊
BIOINFORMATICS
卷 30, 期 3, 页码 301-304出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btt688
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资金
- National Institute of General Medical Sciences [P50GM081892]
- Searle Funds at The Chicago Community Trust from the Chicago Biomedical Consortium
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.
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