A survey of best practices for RNA-seq data analysis

2016· review· en· 2,886 citations· W2236822143 on OpenAlex· 10.1186/s13059-016-0881-8

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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.

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The record

Venue: Genome biology
Topic: Genomics and Phylogenetic Studies
Field: Biochemistry, Genetics and Molecular Biology
Canadian institutions: Simon Fraser University
Funders: National Institute of General Medical SciencesEuropean Regional Development FundNational Key Research and Development Program of ChinaSeventh Framework ProgrammeMedical Research CouncilScience for Life LaboratoryÅbo AkademiSimon Fraser UniversitySigrid Juséliuksen SäätiöTsinghua National Laboratory for Information Science and TechnologyUniwersytet im. Adama Mickiewicza w PoznaniuKarolinska InstitutetTurun YliopistoAcademy of FinlandTsinghua UniversityWellcome TrustHelsingin Yliopisto
Keywords: RNA-SeqBiologyComputational biologyExpression quantitative trait lociTranscriptomeFunctional genomicsGenomicsRNARNA splicingAlternative splicingGenePipeline (software)GeneticsGene expressionGenomeComputer scienceExonSingle-nucleotide polymorphism
Has abstract in OpenAlex: yes
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