Format

Send to

Choose Destination
Methods Mol Biol. 2016;1366:99-114. doi: 10.1007/978-1-4939-3127-9_9.

RNA-Seq Experiment and Data Analysis.

Author information

1
McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
2
Department of Biology, University of South Dakota, 414 E. Clark Street, Vermillion, SD, 57069, USA. Erliang.Zeng@usd.edu.
3
Department of Computer Science, University of South Dakota, 414 E. Clark Street, Vermillion, SD, 57069, USA. Erliang.Zeng@usd.edu.

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.

KEYWORDS:

Bioconductor; Data analysis; Differentially expressed genes; Next-generation sequencing; RNA-Seq; Statistical analysis

PMID:
26585130
DOI:
10.1007/978-1-4939-3127-9_9
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Springer
Loading ...
Support Center