Statistical Methods for Identifying Differentially Expressed Genes in RNA-Seq Experiments

Overview

Journal Cell Biosci

Publisher Biomed Central

Specialty Biology

Date 2012 Aug 2

PMID 22849430

Citations 20

Authors

Zhide Fang

Jeffrey Martin

Zhong Wang

Affiliations

Soon will be listed here.

Abstract

RNA sequencing (RNA-Seq) is rapidly replacing microarrays for profiling gene expression with much improved accuracy and sensitivity. One of the most common questions in a typical gene profiling experiment is how to identify a set of transcripts that are differentially expressed between different experimental conditions. Some of the statistical methods developed for microarray data analysis can be applied to RNA-Seq data with or without modifications. Recently several additional methods have been developed specifically for RNA-Seq data sets. This review attempts to give an in-depth review of these statistical methods, with the goal of providing a comprehensive guide when choosing appropriate metrics for RNA-Seq statistical analyses.

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