Data Analysis Pipeline for RNA-seq Experiments: From Differential Expression to Cryptic Splicing.

Data Analysis Pipeline for RNA-seq Experiments: From Differential Expression to Cryptic Splicing. Curr Protoc Bioinformatics. 2017 Sep 13;59:11.15.1-11.15.21 Authors: Yalamanchili HK, Wan YW, Liu Z 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. PMID: 28902396 [PubMed - in process]
Source: Current Protocols in Bioinformatics - Category: Bioinformatics Tags: Curr Protoc Bioinformatics Source Type: research