Visualizing data from PULSE + comparing probabilities of protein stability from alternative splicing data. For use in tandem with PULSE pipeline from this paper: Semi-supervised Learning Predicts Approximately One Third of the Alternative Splicing Isoforms as Functional Proteins.
From PULSE, copy over the pfam_done.out and elm_read.out from the pulse/output/features/<cell_line> directory into the pulse-data-viz/data directory. Do the same for names.txt and PULSE_Output.txt in pulse/output/machine/<cell_line>.
Finally, run pulse-data-viz/helpers/get_transcript_and_score.py. You're now ready to visualize the data.
git clone https://github.com/wonjunetai/pulse-data-viz.git
cd pulse-data-viz
python -m SimpleHTTPServer 8080 # start python server
Check out the visualization at localhost:8080.