Detection and visualization of differential splicing in RNA-Seq data with JunctionSeq

Although RNA-Seq data provide unprecedented isoform-level expression information, detection of alternative isoform regulation (AIR) remains difficult, particularly when working with an incomplete transcript annotation. We introduce JunctionSeq, a new method that builds on the statistical techniques...

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Main Authors:	Hartley, Stephen W., Mullikin, James C.
Format:	Online
Language:	English
Published:	Oxford University Press 2016
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5009739/

id	pubmed-5009739
recordtype	oai_dc
spelling	pubmed-50097392016-09-07 Detection and visualization of differential splicing in RNA-Seq data with JunctionSeq Hartley, Stephen W. Mullikin, James C. Methods Online Although RNA-Seq data provide unprecedented isoform-level expression information, detection of alternative isoform regulation (AIR) remains difficult, particularly when working with an incomplete transcript annotation. We introduce JunctionSeq, a new method that builds on the statistical techniques used by the well-established DEXSeq package to detect differential usage of both exonic regions and splice junctions. In particular, JunctionSeq is capable of detecting differential usage of novel splice junctions without the need for an additional isoform assembly step, greatly improving performance when the available transcript annotation is flawed or incomplete. JunctionSeq also provides a powerful and streamlined visualization toolset that allows bioinformaticians to quickly and intuitively interpret their results. We tested our method on publicly available data from several experiments performed on the rat pineal gland and Toxoplasma gondii, successfully detecting known and previously validated AIR genes in 19 out of 19 gene-level hypothesis tests. Due to its ability to query novel splice sites, JunctionSeq is still able to detect these differences even when all alternative isoforms for these genes were not included in the transcript annotation. JunctionSeq thus provides a powerful method for detecting alternative isoform regulation even with low-quality annotations. An implementation of JunctionSeq is available as an R/Bioconductor package. Oxford University Press 2016-09-06 2016-06-01 /pmc/articles/PMC5009739/ /pubmed/27257077 http://dx.doi.org/10.1093/nar/gkw501 Text en Published by Oxford University Press on behalf of Nucleic Acids Research 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Hartley, Stephen W. Mullikin, James C.
spellingShingle	Hartley, Stephen W. Mullikin, James C. Detection and visualization of differential splicing in RNA-Seq data with JunctionSeq
author_facet	Hartley, Stephen W. Mullikin, James C.
author_sort	Hartley, Stephen W.
title	Detection and visualization of differential splicing in RNA-Seq data with JunctionSeq
title_short	Detection and visualization of differential splicing in RNA-Seq data with JunctionSeq
title_full	Detection and visualization of differential splicing in RNA-Seq data with JunctionSeq
title_fullStr	Detection and visualization of differential splicing in RNA-Seq data with JunctionSeq
title_full_unstemmed	Detection and visualization of differential splicing in RNA-Seq data with JunctionSeq
title_sort	detection and visualization of differential splicing in rna-seq data with junctionseq
description	Although RNA-Seq data provide unprecedented isoform-level expression information, detection of alternative isoform regulation (AIR) remains difficult, particularly when working with an incomplete transcript annotation. We introduce JunctionSeq, a new method that builds on the statistical techniques used by the well-established DEXSeq package to detect differential usage of both exonic regions and splice junctions. In particular, JunctionSeq is capable of detecting differential usage of novel splice junctions without the need for an additional isoform assembly step, greatly improving performance when the available transcript annotation is flawed or incomplete. JunctionSeq also provides a powerful and streamlined visualization toolset that allows bioinformaticians to quickly and intuitively interpret their results. We tested our method on publicly available data from several experiments performed on the rat pineal gland and Toxoplasma gondii, successfully detecting known and previously validated AIR genes in 19 out of 19 gene-level hypothesis tests. Due to its ability to query novel splice sites, JunctionSeq is still able to detect these differences even when all alternative isoforms for these genes were not included in the transcript annotation. JunctionSeq thus provides a powerful method for detecting alternative isoform regulation even with low-quality annotations. An implementation of JunctionSeq is available as an R/Bioconductor package.
publisher	Oxford University Press
publishDate	2016
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5009739/
_version_	1613642335417008128

Detection and visualization of differential splicing in RNA-Seq data with JunctionSeq

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