NAVIP: Unraveling the Influence of Neighboring Small Sequence Variants on Functional Impact Prediction

Jan-Simon Baasner,Andreas Rempel, Dakota Howard,Boas Pucker

bioRxiv(2024)

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摘要
Once a suitable reference sequence has been generated, intraspecific 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 functional consequences. 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). ### Competing Interest Statement JSB, AR, and DH have no competing interests. BP is head of the technology transfer center Plant Genomics and Applied Bioinformatics at iTUBS.
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