2.5 | Interpretation of candidate genetic variants by WES and CNVs by CMA or LD-WGS
Candidate variants were classified according to the standards and guidelines of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP) (Richards et al., 2015). These guidelines recommend classifying variants into five categories: PV, LPV, variant of uncertain significance (VUS), likely benign variant (LBV), and benign variant (BV) based on combined lines of weighted evidences, including population, computational, functional, segregation, de novo , allelic, and other data. To assess the frequency of a variant in a control or general population, we used the KRGDB, which consists of publicly available race-matched control data from WGS of 1100 Korean individuals, as well as other public databases such as the 1000 Genomes Project database, ExAC database, and gnomAD. A primary literature review was conducted using various sources cited in the Human Gene Mutation Database (HGMD) professional version, release 2018.02 (http://www.hgmd.org/), and ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/), as well as PubMed, to determine the potential pathogenicity of all identified variants. Various in silico tools, including SIFT, Polyphen2, and MutationTaster, all of which use missense prediction algorithms, were used to determine the predicted impact of missense change.
To interpret CNVs, we used DGV (http://dgv.tcag.ca/dgv/app/home), DECIPHER (https://decipher.sanger.ac.uk/), and dbVar (https://www.ncbi.nlm.nih.gov/dbvar/) databases as well as OMIM (https://www.omim.org/). In addition, the clinical findings were compared with those reported in the literature.