1 About

CutOneStrand is a short pipeline designed to search for genomic positions that can be used for targeting a specific strand with a cas9. It produces as an output a list of SNPs that can be targeted on purpose after patient genotyping. It has been designed in the context of the study : Functional benefit of CRISPR/Cas9-induced allele deletion for RYR1 dominant mutation and is especially usefull in the context of autosomal dominant disorders. For the moment it is only compatible with spcas9 targeting NGG pam site. But further developments will lead to other cas and pam to be added.

You can reference the study using DOI : 10.1101/2024.01.24.576997

2 Installation

2.1 Requirements

The pipeline requires a Linux sytem with conda properly installed. If not already set up, please refer to the miniconda documentation.

2.2 Get the code

Then clone this repository

    git clone git@github.com:clbenoit/CutOneStrand.git

2.3 Setup configuration

Open main.sh file in scripts folder and replace MYCONDAPATH with your conda path installation. If you don't know where to find it, run :

    echo `which conda` | sed 's/\/bin\/conda//g'

3 How to use

Launch the pipeline : bash scripts/main.sh [args]

############################################ HELP #####################################################

                 CutOneStrand version = 1.0.0

Usage: scripts/main.sh [args...]
Available arguments :

   -g, --gene,           gene to scan for positions to cut on one strand only, ex : RYR1
   -c, --cas,            cas9 you want to use to cut your gene (Only spcas9 available on v1.0)
   -f, --frequence,      Minimal variant frequency in gnomAD v.3 population
   -o, --output,        Output file name to store results in
   -h, --help,          Show this help section

This pipeline was developped at the CHU Grenoble Alpes
Feel free to address any issue at : benoitclement.sand@gmail.com

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4 References

This work would have not been possible without :

• FlashFry: A fast and flexible tool for large-scale CRISPR target design

• JVARKIT: Java utilities for Bioinformatics

• Every tool listed in environments folder