Differential Usage of Exons and Splice Junctions

View the Project on GitHub Stephen Hartley

> v1.5.4 (Revised Thu Mar 30 17:09:17 EDT 2017)

JunctionSeq is a Bioconductor package for detection and visualization of differential usage of exons and splice junctions in High-Throughput, Next-Generation RNA-Seq datasets. The methodology is heavily based on the DEXSeq bioconductor package, originally proposed by Anders, Reyes, and Huber.

One major advantage of JunctionSeq over other similar tools is that it provides a powerful automated tools for generating readable and interpretable plots and tables to facilitate the interpretation of the results. An example results report is available here. An example set of browser tracks from this same dataset is available here, which uses this trackhub.

Issues, bug reports, or feature requests can be posted to the github issues page. The developers can be contacted at JunctionSeq-Contact (at) list.nih.gov.

JunctionSeq is now part of Bioconductor, and is available in the current release (3.3). You can install JunctionSeq using the devel branch of Bioconductor at the JunctionSeq bioconductor page. Alternatively, you can use the installation instructions below to install the most recent version of JunctionSeq onto the current Bioconductor release (3.2).


Note: The example dataset and results are for testing and demonstration purposes only. The samples and annotation have been heavily modified and down-sampled both to test artificial edge cases and to provide smaller and more portable testing files. The results should not be taken as an indication of any biological phenomenon.

For help with individual R functions in the R utility, use the R command:

> help(functionname);

For a full listing of all help topics for the R utility, use the R command:

> help(package="JunctionSeq");


You can cite the JunctionSeq methods paper, now published in Nucleic Acids Research:

Hartley SW, Mullikin JC. Detection and visualization of differential splicing in RNA-Seq data with JunctionSeq. Nucleic Acids Research. 2016 Jun 1. pii: gkw501. doi: 10.1093/nar/gkw501. PubMed PMID: 27257077.


JunctionSeq can be installed automatically in R using the command:


See the FAQ for advanced installation options.

The splice, gene, and exon read-counts required by JunctionSeq can be created using the QoRTs software package, available here.


If you are using the newest bioconductor release (v3.3), then you can install the Bioconductor version of JunctionSeq:


The bioconductor version differs from the GitHub version in that the post-release patches to a given bioconductor release will never add new features (although bugfixes may be added). This is intended to maintain replicability, but also means that the Bioconductor version will lag behind the github version.

In addition, the GitHub version is currently compatible with R versions 3.2 and 3.3, whereas the Bioconductor version requires v3.3.

Note that unless the "major" version number changes (ie, v2.0.0+), all future versions of JunctionSeq (here or on Bioconductor) will ALWAYS maintain full backwards-compatible functionality with all versions 1.0.0 and up.


Another example dataset, used in the vignette, is packaged as an R package, and can be installed with the command:

                  repos = NULL,


This software package is licensed under the GNU-GPL v3:

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.

Portions of this software are "United States Government Work" under the terms of the United States Copyright Act.
It was written as part of the authors' official duties for the United States Government and thus those portions cannot be copyrighted. Those portions of this software are freely available to the public for use without a copyright notice.
Restrictions cannot be placed on its present or future use.

Although all reasonable efforts have been taken to ensure the accuracy and reliability of the software and data, the National Human Genome Research Institute (NHGRI) and the U.S. Government does not and cannot warrant the performance or results that may be obtained by using this software or data. NHGRI and the U.S. Government disclaims all warranties as to performance, merchantability or fitness for any particular purpose.