SkipGuide

Prediction of CRISPR-Cas9 mediated Exon Skipping

Paper: Machine learning based CRISPR gRNA design for therapeutic exon skipping

Installation (Python Package)

pip install cython

pip install git+https://github.com/gifford-lab/skipguide.git

inDelphi requires version scikit-learn version 0.20.0. Although the MMSplice package requires scikit-learn version 0.19.2, it'll still work with version 0.20.0. Make sure version 0.20.0 is installed:

pip install scikit-learn==0.20.0 --no-deps

Example Usage

Please refer to skipguide/skipguide.py for documentation.

from skipguide import SkipGuide

sg = SkipGuide()

intron = 'GTAAGTTATCACCTTCGTGGCTACAGAGTTTCCTTATTTGTCTCTGTTGCCGGCTTATATGGACAAGCATATCACAGCCATTTATCGGAGCGCCTCCGTACACGCTATTATCGGACGCCTCGCGAGATCAATACGATTACCAGCTGCCCTCGTCGACCCAGGTAGCCTGGCGTGACCCCCTCCCGCTGCCCCAG'
exon = 'TTCTTCTCAGATGTGCGGGAGGCCTGATTACACATATAGACACGCGAGCAGCCATCTTTTATAGAATGGGTAGAACCCGTCCTAAGGACTCAGATTGAGCATCGTTTGCTTCTCGAGTACTACCTGGTACAGATGTCTCTTCAAACAG'

seq = intron + exon
splice_acceptor_site = len(intron)
cutsite = len(intron)
gRNA_orientation = '-'

# The predicted percent spliced in of the exon, which measures the fraction of transcripts containing the exon.
# One minus this value gives the predicted exon skipping frequency.
PSI = sg.predict(seq, cutsite, splice_acceptor_site, gRNA_orientation)