Artificial intelligence (AI) and machine learning have significantly influenced many facets of
the healthcare sector. Advancement in technology has paved the way for analysis of big …

Summary The American College of Medical Genetics and Genomics (ACMG)/Association for
Molecular Pathology (AMP) framework for classifying variants uses six evidence categories …

Single nucleotide variants (SNVs) contribute to human genomic diversity. Synonymous
SNVs are previously considered to be “silent,” but mounting evidence has revealed that …

BACKGROUND Transcriptome sequencing (RNA-seq) improves diagnostic rates in
individuals with suspected Mendelian conditions to varying degrees, primarily by directing …

Hereditary disorders are frequently caused by genetic variants that affect pre‐messenger
RNA splicing. Though genetic variants in the canonical splice motifs are almost always …

Neurofibromatosis type 1, characterized by neurofibromas and café-au-lait macules, is one
of the most common genetic disorders caused by pathogenic NF1 variants. Because of the …

PALB2 loss‐of‐function variants confer high risk of developing breast cancer. Here we
present a systematic functional analysis of PALB2 splice‐site variants detected in …

Genetic testing has undergone a revolution in the last decade, particularly with the advent of
next-generation sequencing and its associated reductions in costs and increases in …

It is possible to estimate the prior probability of pathogenicity for germline disease gene
variants based on bioinformatic prediction of variant effect/s. However, routinely used …

Discriminating which nucleotide variants cause disease or contribute to phenotypic traits
remains a major challenge in human genetics. In theory, any intragenic variant can …