Sample size calculation for differential expression analysis of RNA-seq data

Stephanie Page Hoskins, Derek Shyr, Yu Shyr

研究成果: Chapter


The Holy Grail of precision medicine is the comprehensive integration of patient genotypic with phenotypic data to develop personalized disease prevention and treatment strategies. Next-generation sequencing technologies (NGS) and other types of high-throughput assays have exploded in popularity in recent years, thanks to their ability to produce an enormous volume of data quickly and at relatively low cost compared to more traditional laboratory methods. The ability to generate big data brings us one step closer to the realization of precision medicine; nevertheless, across the life cycle of such data, from experimental design to data capture, management, analysis, and utilization, many challenges remain. In this paper, we reviewed and discussed several statistical methods to estimate sample size based on the Poisson and Negative Binomial distributions for RNAseq experimental design.

主出版物標題Frontiers of Biostatistical Methods and Applications in Clinical Oncology
發行者Springer Singapore
出版狀態Published - 2017 10月 3

All Science Journal Classification (ASJC) codes

  • 一般醫學
  • 一般數學
  • 一般社會科學


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