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

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).

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Publication Details

Journal
PLoS Computational Biology
Published
2025-02-18
DOI
https://doi.org/10.1371/journal.pcbi.1012732
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Andreas Rempel, Dakota Howard, Boas Pucker, Jan-Simon Baasner
PLoS Computational Biology
Genomics and Phylogenetic Studies
article

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

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

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).

PLoS Computational BiologyVol. 21(2)
Bielefeld University (DE), Furman University (US), Technische Universität Braunschweig (DE)
Technische Universität Braunschweig
Life in Land
Openalex Percentile: Top 97%
Genomics and Phylogenetic Studies
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NAVIP: Unraveling the influence of neighboring small sequence variants on functional impact prediction — Andreas Rempel, Dakota Howard, et al. · PLoS Computational Biology (2025) | TGRS Research Map | TGRS