Of note: If you've been using FlashFry before version 1.9, the command-line system has changed slightly.

FlashFry is a fast and flexible command-line tool for characterizing large numbers of potential CRISPR target sequences. FlashFry can be used with any genome, and can run against non-traditional model organisms or transcriptomes. If you're looking to characterize a smaller region or would like a nice web interface we recommend the GT-scan or crispor.org websites.

The easiest way to get started it to try out the quick-start procedure to make sure everything works on your system. If everything looks good, there are few more in-depth tutorials to try out various capacities of FlashFry. Thanks to @drivenbyentropy for the Java implementation of the ViennaRNA energy calculations.

links:

• Quick start
• General options documentation
• Scoring methods
• FAQ
• Database format documentation
• Tutorials - on the wiki
  • Call target sites in a FASTA and annotate with BED intervals
  • Create random target sequences and score them against the genome
• Citing FlashFry

Quickstart

First, make sure you're running Java version 8 (type java -version on the command line to see the version). From the UNIX or Mac command line, download the latest release version of the FlashFry jar file:

wget https://github.com/mckennalab/FlashFry/releases/download/1.15/FlashFry-assembly-1.15.jar

Download and then un-gzip the sample data for human chromosome 22:

wget https://raw.githubusercontent.com/aaronmck/FlashFry/master/test_data/quickstart_data.tar.gz
tar xf quickstart_data.tar.gz

Then run the database creation step (this should take a few minutes, it takes ~75 seconds on my laptop):

mkdir tmp
java -Xmx4g -jar FlashFry-assembly-1.15.jar \
 index \
 --tmpLocation ./tmp \
 --database chr22_cas9ngg_database \
 --reference chr22.fa.gz \
 --enzyme spcas9ngg

Now we discover candidate targets and their potential off-target in the test data (takes a few seconds). Here we're using the EMX1 target with some sequence flanking the target site. This flanking sequnce is needed by on-target scoring metrics to fully evaluate the target's efficiency:

java -Xmx4g -jar FlashFry-assembly-1.15.jar \
 discover \
 --database chr22_cas9ngg_database \
 --fasta EMX1_GAGTCCGAGCAGAAGAAGAAGGG.fasta \
 --output EMX1.output

Finally we score the discovered sites (a few seconds):

java -Xmx4g -jar FlashFry-assembly-1.15.jar \
 score \
 --input EMX1.output \
 --output EMX1.output.scored \
 --scoringMetrics doench2014ontarget,doench2016cfd,dangerous,hsu2013,minot \
 --database chr22_cas9ngg_database

There should now be a set of scored sites in the EMX1.output.scored. Success! Now check out the documentation and tutorials for more specific details.

Cite

FlashFry is published in BMC Biology; if you find it useful please cite:

TY  - JOUR
AU  - McKenna, Aaron
AU  - Shendure, Jay
PY  - 2018
DA  - 2018/07/05
TI  - FlashFry: a fast and flexible tool for large-scale CRISPR target design
JO  - BMC Biology
SP  - 74
VL  - 16
IS  - 1
AB  - Genome-wide knockout studies, noncoding deletion scans, and other large-scale studies require a simple and lightweight framework that can quickly discover and score thousands of candidate CRISPR guides targeting an arbitrary DNA sequence. While several CRISPR web applications exist, there is a need for a high-throughput tool to rapidly discover and process hundreds of thousands of CRISPR targets.
SN  - 1741-7007
UR  - https://doi.org/10.1186/s12915-018-0545-0
DO  - 10.1186/s12915-018-0545-0
ID  - McKenna2018
ER  -