DEOGEN2: prediction and interactive visualization of single amino acid variant deleteriousness in human proteins.

ABSTRACT: High-throughput sequencing methods are generating enormous amounts of genomic data, giving unprecedented insights into human genetic variation and its relation to disease. An individual human genome contains millions of Single Nucleotide Variants: to discriminate the deleterious from the benign ones, a variety of methods have been developed that predict whether a protein-coding variant likely affects the carrier individual's health. We present such a method, DEOGEN2, which incorporates heterogeneous information about the molecular effects of the variants, the domains involved, the relevance of the gene and the interactions in which it participates. This extensive contextual information is non-linearly mapped into one single deleteriousness score for each variant. Since for the non-expert u

SUBMITTER: Raimondi D 

PROVIDER: S-EPMC5570203 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature