Abstract

RNA-sequencing (RNA-seq) has a wide variety of applications, but no single analysis pipeline can be used in all cases. We review all of the major steps in RNA-seq data analysis, including experimental design, quality control, read alignment, quantification of gene and transcript levels, visualization, differential gene expression, alternative splicing, functional analysis, gene fusion detection and eQTL mapping. We highlight the challenges associated with each step. We discuss the analysis of small RNAs and the integration of RNA-seq with other functional genomics techniques. Finally, we discuss the outlook for novel technologies that are changing the state of the art in transcriptomics.

Details

Title
A survey of best practices for RNA-seq data analysis
Author
Conesa, Ana; Madrigal, Pedro; Tarazona, Sonia; Gomez-Cabrero, David; Cervera, Alejandra; McPherson, Andrew; Michał Wojciech Szcześniak; Gaffney, Daniel J; Elo, Laura L; Zhang, Xuegong; Mortazavi, Ali
Publication year
2016
Publication date
2016
Publisher
Springer Nature B.V.
ISSN
14747596
e-ISSN
1474760X
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2208217846
Copyright
© 2016. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.