This repository contains the whole-genome CRISPR target detection method as implemented in Sunagawa et al., "Mammalian Reverse Genetics without Crossing Reveals Nr3a as a Short-Sleeper Gene", Cell Reports 14(3.662-677, 2016)

• Python 2.7

• FASTA formatted chromosome files (obtainable via UCSC.

  • Place these files in a new directory mm10_input/chr_sequences.

  • Concatenate all sequences into a single file named all_sequences.txt

  • Build Bowtie2 indexes for these

• refGene annotation data (obtainable via UCSC)

  • Place this file in the mm10_input directory and name the file refGene.txt

1. Clone this repository

git clone https://github.com/bmds-lab/mm10db.git

2. Build the findMismatches_threads binary

cd <repo>
make pthread

1. Prepare gene lists. This will generate file(s) in the mm10_input directory.

python prepareGeneListsWholeGenome.py 

2. Create list(s) of exons. Repeat for each list file generated in step 1.

python createListExons.py <listFile>

<listFile> is a file generated by createListExons.py. Use only the filename; strip the directory and file extension.

3. Prepare the exon sequences files. Repeat for each list file generated in step 1.

python prepareExonSequences.py <listFile>

<listFile> is a file generated by createListExons.py. Use only the filename; strip the directory and file extension.

4. Prepare list of off-target sites

python prepareListOfftargetSites.py

5. Run method

python target_identitification_viaC.py nb_threads_C=<int> nb_threads_Bowtie=<int> genes=<listFile>

Note: we set nb_threads_C to 128 and nb_threads_Bowtie to 8

<listFile> is a file generated by createListExons.py. Use only the filename; strip the directory and file extension.

If you use this software, please cite the paper.

Sunagawa, G. A., Sumiyama, K., Ukai-Tadenuma, M., Perrin, D., Fujishima, H., Ukai, H., ... & Shimizu, Y. (2016). Mammalian reverse genetics without crossing reveals Nr3a as a short-sleeper gene. Cell reports, 14(3), 662-677.

See LICENSE