RNA测序实验的实验设计与功效计算

Experimental Design and Power Calculation for RNA-seq Experiments.

作者信息

Wu Zhijin, Wu Hao

机构信息

Department of Biostatistics, Brown University, Providence, RI, USA.

Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA.

出版信息

Methods Mol Biol. 2016;1418:379-90. doi: 10.1007/978-1-4939-3578-9_18.

DOI:10.1007/978-1-4939-3578-9_18

PMID:27008024

Abstract

Power calculation is a critical component of RNA-seq experimental design. The flexibility of RNA-seq experiment and the wide dynamic range of transcription it measures make it an attractive technology for whole transcriptome analysis. These features, in addition to the high dimensionality of RNA-seq data, bring complexity in experimental design, making an analytical power calculation no longer realistic. In this chapter we review the major factors that influence the statistical power of detecting differential expression, and give examples of power assessment using the R package PROPER.

摘要

功效计算是RNA测序实验设计的关键组成部分。RNA测序实验的灵活性以及它所测量的转录本的广泛动态范围，使其成为全转录组分析的一项有吸引力的技术。这些特性，再加上RNA测序数据的高维度性，给实验设计带来了复杂性，使得分析功效计算不再现实。在本章中，我们回顾了影响检测差异表达统计功效的主要因素，并给出了使用R包PROPER进行功效评估的示例。