SNAP

SNAP predicts the functional consequences of single amino acid substitutions (non-synonymous single nucleotide polymorphisms, nsSNPs) on protein function to classify variants as neutral or deleterious.

Key Features:

• SNAP methodology: Implements the SNAP (screening for non-acceptable polymorphisms) methodology for variant effect prediction.
• Prediction output: Classifies single amino acid substitutions as neutral or deleterious using a default decision threshold.
• Performance metrics: At its default threshold it correctly identifies over 80% of non-neutral mutations with 77% accuracy and over 76% of neutral mutations with 80% accuracy.
• Reliability index: Provides a per-prediction reliability index that correlates with prediction accuracy.
• High-throughput screening: Supports high-throughput analysis of amino acid substitutions for variant prioritization.
• Human nsSNP focus: Applicable to analysis of non-synonymous SNPs in humans.

Scientific Applications:

• Variant effect interpretation: Evaluating functional impacts of nsSNPs on protein function.
• Disease mechanism elucidation: Prioritizing variants to investigate contributions to disease mechanisms.
• Experimental prioritization: Ranking candidate substitutions for experimental validation using the reliability index.
• Functional genomics and personalized medicine: Enabling high-throughput screening to support functional genomics studies and personalized medicine investigations.

Methodology:

Uses the SNAP (screening for non-acceptable polymorphisms) algorithm to classify single amino acid substitutions at a default threshold and reports a per-prediction reliability index.