A survey of best practices for RNA-seq data analysis

Обзор лучших практик анализа данных RNA-seq
Daniel J. Gaffney, Laura L. Elo, A Mortazavi, Ana Conesa, Pedro Madrigal, Sonia Tarazona, David Gómez-Cabrero, Alejandra Cervera, Andrew McPherson, Michał Wojciech Szcześniak, Xuegong Zhang
2016-01-26

RNA-seq data analysisalternative splicingdifferential gene expressioneQTL mappingread alignment
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.
1
Analysis of small RNAs and integration of RNA-seq with other functional genomics techniques are important complementary approaches.
2
Downstream analyses such as visualization, differential expression, alternative splicing, functional analysis, gene fusion detection, and eQTL mapping each present distinct challenges.
3
Emerging novel technologies are changing transcriptomics and will affect future RNA-seq analysis practices.
4
Major steps requiring careful attention include experimental design, quality control, read alignment, and quantification of gene/transcript levels.
5
No single RNA-seq analysis pipeline fits all applications; analysis must be tailored to specific study goals.

RNA-sequencing (RNA-seq) data analysis workflow

Best practices and methodological considerations across major RNA-seq analysis steps (experimental design, QC, read alignment, quantification, visualization, differential expression, alternative splicing, functional analysis, fusion detection, eQTL mapping, small RNA analysis, and integration with other functional genomics)

Publication Details
Publication Date
2016-01-26
Journal
Publisher
ISSN
Access Type
Author Information
Authors
Daniel J. Gaffney
Laura L. Elo
A Mortazavi
Ana Conesa
Pedro Madrigal
Sonia Tarazona
David Gómez-Cabrero
Alejandra Cervera
Andrew McPherson
Michał Wojciech Szcześniak
Xuegong Zhang
Explore further
Open the scid.ai AI chat with a ready-made request: it will find papers on a similar topic and help build a literature review.
Find similar papers in the chat
Make a presentation
100%