Neighborhood-Aware Variant Impact Predictor

Neighborhood-Aware Variant Impact Predictor predicts functional consequences of genetic variants within protein-coding sequences by considering all variants in a sequence simultaneously to account for interactions between adjacent variants.

Key Features:

• Neighborhood-aware analysis: Considers all variants within a coding sequence simultaneously rather than evaluating each variant independently.
• Adjacent-variant integration: Integrates multiple adjacent variants to assess their collective impact on protein function.
• Interaction-aware prediction: Accounts for modifying interactions between neighboring variants, including enhancement or compensation of effects.
• Structural-annotation incorporation: Uses structural annotations such as gene models to map variants and predict changes in encoded proteins.
• Comparator addressing: Addresses limitations of per-variant predictors such as SnpEff by modeling combined variant effects.
• Cross-species applicability: Applicable to any organism with available reference sequences and structural annotations.

Scientific Applications:

• Intraspecific variation analysis: Improves interpretation of intraspecific genetic variation by predicting collective variant impacts on proteins.
• Protein-coding impact prediction: Enables more accurate prediction of changes in encoded proteins when multiple sequence variants are present.
• Model organism demonstration: Applied in a proof-of-concept study on Arabidopsis thaliana accessions Columbia-0 and Niederzenz-1.

Methodology:

Integrates multiple adjacent variants per coding sequence and uses structural annotations (gene models) to predict their collective impacts on encoded proteins, accounting for variant interactions.