title: Sample size calculation based on exact test for assessing differential expression analysis in RNA-seq data.
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.
authors: Chung-I
authors: CI
authors: Li
authors: Pei-Fang
authors: PF
authors: Su
authors: Center for Quantitative Sciences, Vanderbilt University, 571 Preston Building Nashville, TN, USA. yu.shyr@vanderbilt.edu.
authors: Yu
authors: Y
authors: Shyr
mesh_terms: D001483:Base Sequence; D003198:Computer Simulation / Q000706:statistics & numerical data; D005786:Gene Expression Regulation; D016013:Likelihood Functions; D015233:Models, Statistical; D016012:Poisson Distribution; D012313:RNA / Q000037:antagonists & inhibitors / Q000096:biosynthesis* / Q000235:genetics*; D011897:Random Allocation; D012107:Research Design / Q000706:statistics & numerical data / Q000639:trends; D018401:Sample Size; D017423:Sequence Analysis, RNA / Q000379:methods* / Q000706:statistics & numerical data / Q000639:trends; D014584:User-Computer Interface
chemical_list: D012313:RNA