Sample size calculation based on exact test for assessing differential expression analysis in RNA-seq data

BMC Bioinformatics. 2013 Dec 6:14:357. doi: 10.1186/1471-2105-14-357.

Abstract

Background: Sample size calculation is an important issue in the experimental design of biomedical research. For RNA-seq experiments, the sample size calculation method based on the Poisson model has been proposed; however, when there are biological replicates, RNA-seq data could exhibit variation significantly greater than the mean (i.e. over-dispersion). The Poisson model cannot appropriately model the over-dispersion, and in such cases, the negative binomial model has been used as a natural extension of the Poisson model. Because the field currently lacks a sample size calculation method based on the negative binomial model for assessing differential expression analysis of RNA-seq data, we propose a method to calculate the sample size.

Results: We propose a sample size calculation method based on the exact test for assessing differential expression analysis of RNA-seq data.

Conclusions: The proposed sample size calculation method is straightforward and not computationally intensive. Simulation studies to evaluate the performance of the proposed sample size method are presented; the results indicate our method works well, with achievement of desired power.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • Base Sequence
  • Computer Simulation / statistics & numerical data
  • Gene Expression Regulation*
  • Likelihood Functions
  • Models, Statistical
  • Poisson Distribution
  • RNA / antagonists & inhibitors
  • RNA / biosynthesis*
  • RNA / genetics*
  • Random Allocation
  • Research Design / statistics & numerical data
  • Research Design / trends
  • Sample Size
  • Sequence Analysis, RNA / methods*
  • Sequence Analysis, RNA / statistics & numerical data
  • Sequence Analysis, RNA / trends
  • User-Computer Interface

Substances

  • RNA