The Future of Clinical Diagnosis

Sequencing techniques are limited by the interpretation of a large number of coding and noncoding, sequence and structural, variants. In-silico tools for predicting the impact of coding variants and regulatory elements have become increasingly advanced. However, the evidence from these tools is generally not sufficient for accurate variant classification. In this article, the authors discuss a multi-omic approach that they foresee will enable genome-wide characterization and classification of variants by integrating several omics data, assisted by bioinformatics tools and deep learning algorithms for variant prioritization.
Source: Clinics in Laboratory Medicine - Category: Laboratory Medicine Authors: Source Type: research