Insights on variant analysis in silico tools for pathogenicity prediction
Felipe Antônio de Oliveira Garcia, Edilene Santos de Andrade, Edenir Inêz Palmero
Abstract
Molecular biology is currently a fast-advancing science. Sequencing techniques are getting cheaper, but the interpretation of genetic variants requires expertise and computational power, therefore is still a challenge. Next-generation sequencing releases thousands of variants and to classify them, researchers propose protocols with several parameters. Here we present a review of several in silico pathogenicity prediction tools involved in the variant prioritization/classification process used by some international protocols for variant analysis and studies evaluating their efficiency.
Topics & Concepts
In silicoPathogenicityPrioritizationComputational biologyComputer scienceDNA sequencingMachine learningBiologyGeneticsGeneManagement scienceEngineeringMicrobiologyGenomics and Phylogenetic StudiesGenomics and Rare DiseasesGene expression and cancer classification