A Survey of Best Practices for RNA-seq Data Analysis
View / Open Files
Authors
Conesa, Ana
Tarazona, Sonia
Gomez-Cabrero, David
Cervera, Alejandra
McPherson, Andrew
Wojciech, Szcześniak Michał
Gaffney, Daniel
Elo, Laura L
Zhang, Xuegong
Mortazavi, Ali
Publication Date
2016-01-26ISSN
1474-7596
Publisher
BioMed Central
Volume
17
Number
13
Language
English
Type
Article
Metadata
Show full item recordCitation
Conesa, A., Madrigal, P., Tarazona, S., Gomez-Cabrero, D., Cervera, A., McPherson, A., Wojciech, S. M., et al. (2016). A Survey of Best Practices for RNA-seq Data Analysis. 17 (13)https://doi.org/10.1186/s13059-016-0881-8
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 major steps of 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 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.
Keywords
RNA-seq, Next-generation sequencing, transcriptomics, differential gene expression, guidelines, standards
Sponsorship
MRC (MC_PC_12009)
Identifiers
External DOI: https://doi.org/10.1186/s13059-016-0881-8
This record's URL: https://www.repository.cam.ac.uk/handle/1810/253244
Rights
Attribution 2.0 UK: England & Wales, Creative Commons Attribution License 2.0 UK
Licence URL: http://creativecommons.org/licenses/by/2.0/uk/