Score and rank guide RNA candidates for CRISPR experiments based on efficiency prediction algorithms and sequence analysis
Efficiency Score
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GC Content
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Melting Temperature
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Specificity Score
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Recommendation
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Scores above 7.5 indicate high efficiency gRNAs that are likely to perform well in experiments. Scores between 5-7.5 are moderate efficiency, while scores below 5 suggest poor performance.
The tool uses machine learning algorithms trained on experimental data to predict guide RNA efficiency. It considers sequence features, thermodynamics, and potential off-target effects to generate comprehensive scores.
Key factors include GC content (optimal 40-60%), position-specific nucleotide preferences, thermodynamic stability, secondary structure formation, and PAM accessibility.
Yes, off-target analysis is crucial for ensuring specificity. High-scoring guides with potential off-targets may cause unintended edits, so balance efficiency with specificity.
NGG is the most common PAM for SpCas9 and offers good targeting flexibility. Alternative Cas proteins like Cpf1 (TTTN PAM) or SaCas9 (NNGRRT PAM) can access different genomic sites.
Standard guide RNAs are typically 20 nucleotides long, though 19-23 nucleotides can work. The length affects both efficiency and specificity, with 20 nt being optimal for most applications.
Yes, computational predictions should be validated through in vitro or in vivo experiments. Test multiple predicted high-efficiency guides to confirm performance in your specific system.