Title |
FlashFry: a fast and flexible tool for large-scale CRISPR target design
|
---|---|
Published in |
BMC Biology, July 2018
|
DOI | 10.1186/s12915-018-0545-0 |
Pubmed ID | |
Authors |
Aaron McKenna, Jay Shendure |
Abstract |
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. Here, we introduce FlashFry, a fast and flexible command-line tool for characterizing large numbers of CRISPR target sequences. With FlashFry, users can specify an unconstrained number of mismatches to putative off-targets, richly annotate discovered sites, and tag potential guides with commonly used on-target and off-target scoring metrics. FlashFry runs at speeds comparable to commonly used genome-wide sequence aligners, and output is provided as an easy-to-manipulate text file. FlashFry is a fast and convenient command-line tool to discover and score CRISPR targets within large DNA sequences. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 15% |
Venezuela, Bolivarian Republic of | 1 | 8% |
Germany | 1 | 8% |
United Kingdom | 1 | 8% |
Turkey | 1 | 8% |
South Africa | 1 | 8% |
Spain | 1 | 8% |
Unknown | 5 | 38% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 7 | 54% |
Scientists | 4 | 31% |
Practitioners (doctors, other healthcare professionals) | 1 | 8% |
Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 128 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 27 | 21% |
Researcher | 21 | 16% |
Student > Master | 9 | 7% |
Student > Bachelor | 6 | 5% |
Student > Doctoral Student | 5 | 4% |
Other | 16 | 13% |
Unknown | 44 | 34% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 34 | 27% |
Agricultural and Biological Sciences | 22 | 17% |
Computer Science | 9 | 7% |
Medicine and Dentistry | 5 | 4% |
Immunology and Microbiology | 2 | 2% |
Other | 9 | 7% |
Unknown | 47 | 37% |