FlashFry: a Fast and Flexible Tool for Large-scale CRISPR Target Design

Overview

Journal BMC Biol

Publisher Biomed Central

Specialty Biology

Date 2018 Jul 7

PMID 29976198

Citations 63

Authors

Aaron McKenna

Jay Shendure

Affiliations

Soon will be listed here.

Abstract

Background: 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.

Results: 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.

Conclusions: FlashFry is a fast and convenient command-line tool to discover and score CRISPR targets within large DNA sequences.

Citing Articles

Genome-wide CRISPR guide RNA design and specificity analysis with GuideScan2.

Schmidt H, Zhang M, Chakarov D, Bansal V, Mourelatos H, Sanchez-Rivera F Genome Biol. 2025; 26(1):41.

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Benchmarking and optimizing Perturb-seq in differentiating human pluripotent stem cells.

Sivakumar S, Wang Y, Goetsch S, Pandit V, Wang L, Zhao H bioRxiv. 2025; .

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Analysis of single-cell CRISPR perturbations indicates that enhancers predominantly act multiplicatively.

Zhou J, Guruvayurappan K, Toneyan S, Chen H, Chen A, Koo P Cell Genom. 2024; 4(11):100672.

PMID: 39406234 PMC: 11605691. DOI: 10.1016/j.xgen.2024.100672.

Multiplex, single-cell CRISPRa screening for cell type specific regulatory elements.

Chardon F, McDiarmid T, Page N, Daza R, Martin B, Domcke S Nat Commun. 2024; 15(1):8209.

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Codon usage and expression-based features significantly improve prediction of CRISPR efficiency.

Bergman S, Tuller T NPJ Syst Biol Appl. 2024; 10(1):100.

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