title: RNA-Seq Experiment and Data Analysis.
abstract: With the ability to obtain tens of millions of reads, high-throughput messenger RNA sequencing (RNA-Seq) data offers the possibility of estimating abundance of isoforms and finding novel transcripts. In this chapter, we describe a protocol to construct an RNA-Seq library for sequencing on Illumina NGS platforms, and a computational pipeline to perform RNA-Seq data analysis. The protocols described in this chapter can be applied to the analysis of differential gene expression in control versus 17β-estradiol treatment of in vivo or in vitro systems.
authors.affiliation: McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
authors.forename: Hanquan
authors.initials: H
authors.lastname: Liang
authors.affiliation: Department of Biology, University of South Dakota, 414 E. Clark Street, Vermillion, SD, 57069, USA. Erliang.Zeng@usd.edu.|Department of Computer Science, University of South Dakota, 414 E. Clark Street, Vermillion, SD, 57069, USA. Erliang.Zeng@usd.edu.
authors.forename: Erliang
authors.initials: E
authors.lastname: Zeng
mesh_terms: D000818:Animals; D001483:Base Sequence; D019295:Computational Biology; D030541:Databases, Genetic; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D012333:RNA, Messenger / Q000235:genetics*; D017423:Sequence Analysis, RNA; D057188:Workflow
chemical_list: D012333:RNA, Messenger
keywords: Bioconductor; Data analysis; Differentially expressed genes; Next-generation sequencing; RNA-Seq; Statistical analysis