Genetic variant pathogenicity prediction trained using disease-specific clinical sequencing data sets.

ABSTRACT: Recent advances in DNA sequencing have expanded our understanding of the molecular basis of genetic disorders and increased the utilization of clinical genomic tests. Given the paucity of evidence to accurately classify each variant and the difficulty of experimentally evaluating its clinical significance, a large number of variants generated by clinical tests are reported as variants of unknown clinical significance. Population-scale variant databases can improve clinical interpretation. Specifically, pathogenicity prediction for novel missense variants can use features describing regional variant constraint. Constrained genomic regions are those that have an unusually low variant count in the general population. Computational methods have been introduced to capture these regions and inco

SUBMITTER: Evans P 

PROVIDER: S-EPMC6633260 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature