Document Type
Article
Journal/Book Title/Conference
BMC Genomics
Volume
19
Publisher
BMC
Publication Date
12-20-2018
First Page
1
Last Page
13
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Abstract
Background: When genomics researchers design a high-throughput study to test for differential expression, some biological systems and research questions provide opportunities to use paired samples from subjects, and researchers can plan for a certain proportion of subjects to have paired samples. We consider the effect of this paired samples proportion on the statistical power of the study, using characteristics of both count (RNA-Seq) and continuous (microarray) expression data from a colorectal cancer study.
Results: We demonstrate that a higher proportion of subjects with paired samples yields higher statistical power, for various total numbers of samples, and for various strengths of subject-level confounding factors. In the design scenarios considered, the statistical power in a fully-paired design is substantially (and in many cases several times) greater than in an unpaired design.
Conclusions: For the many biological systems and research questions where paired samples are feasible and relevant, substantial statistical power gains can be achieved at the study design stage when genomics researchers plan on using paired samples from the largest possible proportion of subjects. Any cost savings in a study design with unpaired samples are likely accompanied by underpowered and possibly biased results.
Recommended Citation
Stevens, John R., Herrick, Jennifer S., Wolff, Roger K., and Slattery, Martha L. "Power in Pairs: Assessing the Statistical Value of Paired Samples in Tests for Differential Expression." BMC Genomics, vol. 19, 2018, pp. 1-13. https://doi.org/10.1186/s12864-018-5236-2
