INTRODUCTION

The sgRNAcas9-AI command-line software tool can be used to optimize the design of sgRNAs in CRISPR/Cas9 systems, including deep learning-based strategies for sgRNA activity prediction and assessment of potential off-target sites. In a nutshell, the features of sgRNAcas9-AI:

- sgRNA activity prediction based on deep learning strategy

- Evaluation of sgRNA potential off-target sites based on sequence alignment strategy

INSTALLATION

This tool can only be run on Linux systems, the steps to install the necessary dependencies for the program are as follows:

1.python3

Linux：[https](https://www.python.org/downloads/source/) ://www.python.org/downloads/source/

2.Install pip (pip should come with Python, but this should ensure it is present; see https://pip.pypa.io/en/stable/installation/)

3.Install package

pip install regex

pip install numpy

pip install pandas

pip install tensorflow

4.Verify that sgRNAcas9-AI is installed using the command:

python sgRNAcas9-AI.py --help

USAGE INFORMATION

sgRNAcas9-AI requires main two parameters:

- input sequences in the form of fasta files (given by the `-i` or `--input`)

- reference genome in the form of fasta files (given by the `-g` or `--genome`).

For example:

python sgRNACas9-AI.py -i gene.fa -g genome.fa -a -m 3 -p NGG -t 8 -o result.txt

Parameter list

-h or --help: show a help message and exit.

--version: show program version

-i or --input: input sequences in fasta files

-g or --genome: genome sequences in fasta files

-a or --active: predict sgRNA activity

-m or --mismatch: mismatch number of sgRNA off-target prediciton

-p or --pam: specify th pam to use for off-target analysis

-t or --thread: the number of processes to use for program

-o or --output: output file for result