A Two-Stage Poisson Model for Testing RNA-Seq Data
A Two-Stage Poisson Model for Testing RNA-Seq Data
复制标题
DOI：
10.2202/1544-6115.1627
复制
发表时间：
2011-01-01
影响因子：
0.9
通讯作者：
Doerge, Rebecca W.
中科院分区：
文献类型：
--
作者：
Auer, Paul L.;Doerge, Rebecca W.
RNA测序技术正在提供前所未有的高通量、高分辨率和高精度的数据。尽管有许多不同的计算工具用于处理这些数据，但用于分析它们的统计方法却很有限，而能够认识到单个基因转录独特性质的方法就更少了。我们引入一种简单而强大的基于两阶段泊松模型的统计方法，用于对RNA测序数据进行建模，并检测基因表达中具有生物学重要性的变化。通过模拟和实际数据应用展示了这种方法的优势。
RNA sequencing technology is providing data of unprecedented throughput, resolution, and accuracy. Although there are many different computational tools for processing these data, there are a limited number of statistical methods for analyzing them, and even fewer that acknowledge the unique nature of individual gene transcription. We introduce a simple and powerful statistical approach, based on a two-stage Poisson model, for modeling RNA sequencing data and testing for biologically important changes in gene expression. The advantages of this approach are demonstrated through simulations and real data applications.