Detection and Visualization of Differential Splicing in RNA-Seq Data with JunctionSeq
Stephen W. Hartley, James C. Mullikin

TL;DR
JunctionSeq is a novel method for detecting differential isoform regulation in RNA-Seq data, especially effective with incomplete annotations, by analyzing exonic regions and splice junctions without needing isoform assembly.
Contribution
It introduces JunctionSeq, a new statistical approach that detects differential usage of exons and splice junctions, including novel junctions, improving AIR detection with flawed annotations.
Findings
Successfully detected known AIR genes in multiple experiments.
Capable of identifying differential splicing without complete isoform annotation.
Provides an intuitive visualization toolkit for results interpretation.
Abstract
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 differentials in 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…
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