ngg2

Python package to identify NGGNGG Cas9 gRNA sites in any indexed FASTA file.

It is important to note that sites are identified using regular expressions (re). In standard mode, the sites are searched exhaustively.

In block scan mode, once characters are consumed in a match, they're gone. That means block scan only reports the first encountered gRNA site, but not second sites on the same strand that overlap it.

Installation

is available via pip or GitHub download. We HIGHLY recommend installing in a Python virtual environment.

pip install ngg2

Or user install

pip install --user ngg2

Or install from GitHub clone.

git clone https://github.com/RobersonLab/ngg2.git
git checkout vN.N.N # Choose highest version tag instead of vN.N.N

pip install -e .

Depends on

• Python (tested on Python 2.7, 3.2-3.5)
• FASTA file of genome / contig of interest
• pyfaidx
• regex

Usage

Find gRNA sites for in the first 10M bp of human chromosome 1.

ngg2 --outputFile myOutput.csv --region 1:1-10000000 human_genome.fa

Find all gRNA sites in a FASTA file.

ngg2 --outputFile myOutput.csv human_genome.fa

Find all gRNA sites in a FASTA file, but allow non-canonical (A, T, C) starting bases.

ngg2 --outputFile myOutput.csv --allowNoncanonical human_genome.fa

Find all gRNA sites in a FASTA file, using 10 processors

ngg2 --outputFile myOutput.csv --cores 10 human_genome.fa

Process in serial and write results to file, leaving out uniqueness of gRNA site

ngg2 --outputFile myOutput.csv --unbuffered human_genome.fa

Process in parallel, skipping uniqueness tests

ngg2 --outputFile myOutput.csv --cores 10 --skipUniqueScan human_genome.fa

Don't print log info

ngg2 --outputFile myOutput.csv --loglevel CRITICAL