Data Analysis Pipeline for RNA‐seq Experiments: From Differential Expression to Cryptic Splicing. Issue 1 (13th February 2018)

• Record Type: Journal Article
• Authors: Yalamanchili, Hari Krishna; Wan, Ying‐Wooi; Liu, Zhandong
• Editors: Baxevanis, Andreas D.; Petsko, Gregory A.; Stein, Lincoln D.; Stormo, Gary D.
• Is Part Of: Current protocols in bioinformatics. Volume 59:Issue 1(2017)
• Page Start: 11.15.1
• Page End: 11.15.21
• Publication Date: 2018-02-13
• Subjects: RNA‐seq -- differential gene expression -- differential isoform usage -- alternative splicing -- cryptic splicing; Bioinformatics -- Laboratory manuals; Nucleotide sequence -- Laboratory manuals; Amino acid sequence -- Laboratory manuals; Base Sequence; Amino Acid Sequence; Computational Biology -- methods; Databases, Genetic; Proteins -- analysis; Sequence Analysis -- methods; Sequence Homology; Amino acid sequence; Bioinformatics; Nucleotide sequence; Laboratory Manuals; Laboratory manuals; 570.285
• DOI: 10.1002/cpbi.33
• Languages: English
• ISSNs: 1934-3396

Abstract

Abstract: RNA sequencing (RNA‐seq) is a high‐throughput technology that provides unique insights into the transcriptome. It has a wide variety of applications in quantifying genes/isoforms and in detecting non‐coding RNA, alternative splicing, and splice junctions. It is extremely important to comprehend the entire transcriptome for a thorough understanding of the cellular system. Several RNA‐seq analysis pipelines have been proposed to date. However, no single analysis pipeline can capture dynamics of the entire transcriptome. Here, we compile and present a robust and commonly used analytical pipeline covering the entire spectrum of transcriptome analysis, including quality checks, alignment of reads, differential gene/transcript expression analysis, discovery of cryptic splicing events, and visualization. Challenges, critical parameters, and possible downstream functional analysis pipelines associated with each step are highlighted and discussed. This unit provides a comprehensive understanding of state‐of‐the‐art RNA‐seq analysis pipeline and a greater understanding of the transcriptome. © 2017 by John Wiley & Sons, Inc.