# NAVIP: Unraveling the influence of neighboring small sequence variants on functional impact prediction

## TL;DR

NAVIP improves variant impact predictions by considering neighboring sequence variants in protein coding regions.

## Contribution

NAVIP introduces a novel method for variant impact prediction by incorporating neighboring variants in a protein coding sequence.

## Key findings

- NAVIP considers all variants within a protein coding sequence to improve functional impact predictions.
- The method was tested using variants between Arabidopsis thaliana accessions Columbia-0 and Niederzenz-1.

## Abstract

Once a suitable reference sequence has been generated, intra-species variation is often assessed by re-sequencing. Variant calling processes can reveal all differences between strains, accessions, genotypes, or individuals. These variants can be enriched with predictions about their functional implications based on available structural annotations, i.e., gene models. Although these functional impact predictions on a per-variant basis are often accurate, some challenging cases require the simultaneous incorporation of multiple adjacent variants into this prediction process. Examples include neighboring variants which modify each other’s functional impact. The Neighborhood-Aware Variant Impact Predictor (NAVIP) considers all variants within a given protein coding sequence when predicting the effect. As a proof of concept, variants between the Arabidopsis thaliana accessions Columbia-0 and Niederzenz-1 were annotated. NAVIP is freely available on GitHub (https://github.com/bpucker/NAVIP) and accessible through a web server (https://pbb-tools.de).