mvPPT: A Highly Efficient and Sensitive Pathogenicity Prediction Tool for Missense Variants.
Genomics Proteomics Bioinformatics
; 21(2): 414-426, 2023 04.
Article
em En
| MEDLINE
| ID: mdl-35940520
ABSTRACT
Next-generation sequencing technologies both boost the discovery of variants in the human genome and exacerbate the challenges of pathogenic variant identification. In this study, we developed Pathogenicity Prediction Tool for missense variants (mvPPT), a highly sensitive and accurate missense variant classifier based on gradient boosting. mvPPT adopts high-confidence training sets with a wide spectrum of variant profiles, and extracts three categories of features, including scores from existing prediction tools, frequencies (allele frequencies, amino acid frequencies, and genotype frequencies), and genomic context. Compared with established predictors, mvPPT achieves superior performance in all test sets, regardless of data source. In addition, our study also provides guidance for training set and feature selection strategies, as well as reveals highly relevant features, which may further provide biological insights into variant pathogenicity. mvPPT is freely available at http//www.mvppt.club/.
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Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Biologia Computacional
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Mutação de Sentido Incorreto
Tipo de estudo:
Diagnostic_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article