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A survey of best practices for RNA-seq data analysis.

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cam.issuedOnline2016-01-26
dc.contributor.authorConesa, Ana
dc.contributor.authorMadrigal, Pedro
dc.contributor.authorTarazona, Sonia
dc.contributor.authorGomez-Cabrero, David
dc.contributor.authorCervera, Alejandra
dc.contributor.authorMcPherson, Andrew
dc.contributor.authorSzcześniak, Michał Wojciech
dc.contributor.authorGaffney, Daniel J
dc.contributor.authorElo, Laura L
dc.contributor.authorZhang, Xuegong
dc.contributor.authorMortazavi, Ali
dc.contributor.orcidMadrigal, Pedro [0000-0003-1959-8199]
dc.date.accessioned2016-01-13T17:47:10Z
dc.date.available2016-01-13T17:47:10Z
dc.date.issued2016-01-26
dc.description.abstractRNA-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.
dc.description.versionThis is the final published version. It first appeared at http://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0881-8.
dc.identifier.citationGenome Biology 2016 17:13. DOI: 10.1186/s13059-016-0881-8
dc.identifier.eissn1474-760X
dc.identifier.issn1474-7596
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/253244
dc.languageEnglish
dc.language.isoeng
dc.publisherSpringer Science and Business Media LLC
dc.publisher.urlhttp://dx.doi.org/10.1186/s13059-016-0881-8
dc.rightsAttribution 2.0 UK: England & Wales
dc.rightsCreative Commons Attribution License 2.0 UK
dc.rights.urihttp://creativecommons.org/licenses/by/2.0/uk/
dc.subjectAlternative Splicing
dc.subjectBase Sequence
dc.subjectGene Expression Profiling
dc.subjectGene Fusion
dc.subjectGenomics
dc.subjectHigh-Throughput Nucleotide Sequencing
dc.subjectRNA
dc.subjectSequence Analysis, RNA
dc.subjectSoftware
dc.titleA survey of best practices for RNA-seq data analysis.
dc.typeArticle
prism.number13
prism.publicationDate2016
prism.publicationNameGenome Biol
prism.volume17
pubs.funder-project-idMedical Research Council (MC_PC_12009)
rioxxterms.licenseref.startdate2016-01-26
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.typeJournal Article/Review
rioxxterms.versionofrecord10.1186/s13059-016-0881-8

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