A multi-processing tool for designing CRISPR guide RNA library. MultiGuideScan parallelizes the workflow of GuideScan (https://bitbucket.org/arp2012/guidescan_public) with the multi-processing mechanism and uses the preprocessing optimization method to improve the computational efficiency.
Ensure the following dependencies are present
:::system
samtools 1.3.1
easy_install
coreutils (shuf)
rename
python 2.7
biopython>=1.66
pysam==0.8.3
pyfaidx==0.4.7.1
bx-python==0.7.3
for Rule Set 2 on-target cutting efficiency scores (this must be installed by user: https://pypi.python.org/pypi/scikit-learn/0.16.1)
sklearn==0.16.1
To install, run
:::system
python setup.py install
This will install binaries guidescan_processer
, guidescan_bamdata
, guidescan_guidequery
, guidescan_cutting_efficiency_processer
, guidescan_cutting_efficiency_processer
.
After installation, use
:::python
from guidescan import *
in your python session to import all modules of the package, or use
:::python
from guidescan import guidequery
to import a particular module and then use functions from the module
:::python
guidequery.query_bam()
For local installation, run something like
:::system
python setup.py install --user
and then make sure that the local directory with binaries (such as $HOME/Library/Python/2.7/bin/
) is available in your PATH.
For more info on full pipeline of guideRNA database construction from genomic sequences run
:::system
guidescan_processer -h
For more info on guideRNA database construction with custom parameters using previously computed trie run
:::system
guidescan_bamdata -h
For more info on accessing precomputed guideRNA database run
:::system
guidescan_guidequery -h
For more info on computing cutting efficiency scores for Cas9 20mer gRNAs
:::system
guidescan_cutting_efficiency_processer -h
For more info on computing cutting specificity scores for Cas9 20mer gRNAs
:::system
guidescan_cutting_specificity_processer -h