Visualisation of long read RNA-Seq splicing

Question

I have a dataset of Oxford Nanopore cDNA reads. Many of my reads are full-length or close to full-length transcripts, and I and am interested in examining alternative splicing. For this, I would like to begin by visualising my reads and comparing variants qualitatively.

I have tried visualising my data in both IGV and SeqMonk, but neither has given a satisfying result.

IGV

IGV shows some links between aligned sections, shown as fine blue lines and thick black lines. I cannot work out what the difference between these lines is, and even more confusingly, we have numerous alignments where two aligned exons come from the same sequence but are not joined by any line. This means that, to confirm or deny a spliced variant, I need to manually examine the read ID of each exon.

SeqMonk

SeqMonk gives a much cleaner visualisation, but unfortunately shows no links between aligned exons, and worse, I cannot find the read IDs. This means there is functionally (as far as I can see) no way to tell which exons come from the same read.

EDIT: Sashimi Plot

As recommended in this answer, I have tried using IGV's Sashimi Plot. Unfortunately, I believe the high error rate and relatively low coverage is causing this to create somewhat confusing output. The Sashimi Plot shows mostly nearly every junction to have just a single read supporting it.

Is there a visualisation tool which allows simple examination of splicing of full-length transcripts?

Answer 1

DNASTAR's software is for purchase, but high quality. GenVision Pro does genomic visualization, including Sashimi plots.

Edit: not sure why this answer is being downvoted, unless it's because the software isn't free. OP has tried IGV and SeqMonk, I mentioned an alternative he might not have heard of.

Here is a video demonstrating the use of Sashimi plots in GenVision Pro:

http://www.dnastar.com/t-support-videos.aspx?video=YJvcERoSIsg

Answer 2

The Sashmi Plot feature built into IGV. It gives a nice summary of the spliced transcripts and the coverage of each exon.

For example:

Answer 3

IGB gives the intended result without much hassle. It doesn't have the bells and whistles of IGV, but presents a clean and intuitive view of the individual reads.

In IGB, each read is presented as a single, contiguous line.

If you zoom in you can see the read ID for each read.

For a more holistic view, IGV's Sashimi plot can be modified to exclude spurious junctions supported by few reads. Here is a section of the above gene with default settings:

The minimum junction coverage can be set by right-clicking on the Sashimi plot itself, or application-wide under View -> Preferences -> Alignments -> Splice Junction Track Options. With minimum junction coverage 3, the noisy plot above now looks like this:

The numbers are still hard to read due to numerous overlapping almost-identical junctions, but at least the plot is now readable.