Optimized sgRNA design to maximize activity and minimize off . . . We tested the ability of the CFD score to predict off-target, imperfect-match activity for an independent dataset of 89 sgRNAs designed to target H2-D, some of which were previously shown to produce effective protein knockout of H2-K, a gene with highly similar sequence 9
sgRNA Scoring Help - Broad Institute This tool ranks and picks candidate sgRNA sequences for the targets provided, while attempting to maximize on-target activity and minimizing off-target activity
Deep learning improves the ability of sgRNA off-target . . . Selection of appropriate sgRNA can improve the on-target knockout efficacy of CRISPR Cas9 system with high sensitivity and specificity However, when CRISPR Cas9 system is operating, unexpected cleavage may occur at some sites, known as off-target
GUIDES: sgRNA design for loss-of-function screens - Nature By using exome-wide CFD scoring during design of a library with ∼ 2,000 genes, the percentage of designed sgRNAs with predicted off targets is reduced from ∼ 43% to ∼ 4% (Supplementary Fig
Optimized sgRNA design by deep learning to balance the off- scoring algorithms are MIT Broad score (18) and CFD score (33) Both scoring methods are based on evaluating the contributions made by different mismatch positions and number in the target site, and calculating a weight matrix to determine off-target efficiency of each sgRNA
crisprScore: On-Target and Off-Target Scoring Algorithms for . . . getCFDScores returns a data frame with spacer, protospacer, and score columns The CFD score takes on a value between 0 and 1 For a given pair (on-target, off-target), a higher CFD score indicates a higher likelihood for the nuclease to cut at the off-target Non-canonical PAM sequences are taken into account by the CFD algorithm Author(s)
Off-target effects in CRISPR Cas9 gene editing - PMC The CFD algorithm is derived from a CRISPR Cas9 genetic screen experiment that assessed the off-target effects of thousands of sgRNAs (Doench et al , 2016) DeepCRISPR is a comprehensive computational platform which utilizes deep learning to predict off-target cleavage sites