RegSNPs-intron: A computational framework for predicting pathogenic impact of intronic single nucleotide variants
RegSNPs-intron: A computational framework for predicting pathogenic impact of intronic single nucleotide variants
Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their diseasecausing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure, and evolutionary conservation features.