Visualize coverage, canonical, and backsplice junctions.
See https://splicev.readthedocs.io/en/master/
See https://github.com/flemingtonlab/SpliceV/blob/master/docs/example.pdf
This will generate figure 1B and 1C from our manuscript (DOI pending)
SpliceV works with Python 2.7 and 3.0+.
- Matplotlib
- Numpy
- pysam
To install SpliceV:
pip install SpliceV
Or:
git clone https://github.com/flemingtonlab/SpliceV.git
To run the example dataset:
git clone https://github.com/flemingtonlab/SpliceV.git
cd SpliceV/example
python ../bin/SpliceV -b example.vta1.bam -gtf vta1.gtf -sj example.canonical.bed -bsj example.circles.bed -g VTA1 -f 3 -is 3
The sample data comes from Akata cells (a B Cell Lymphoma line) that were treated with the exonuclease RNase R prior to sequencing. RNase R exclusively digests RNA with a free end, helping enrich circularized RNA abundance in the sample.
These example commands will generate the following plot:
This plot reveals a prominant circle from exon 2 through exon 4 (evidenced by the back-splice junction reads which are plotted as curves below the axis. This is also demonstrated by the higher level of coverage in exon 2-4, shown by the relative intensity of color).
The major circularized isoform (exons 2-4; another less prevalent circle appears to include exon 5) is isolated below:
Created by Nathan Ungerleider and Erik Flemington