I am involved in WP4 through the development of a pilot project to enable the identification of prioritization of variants within the noncoding regions of the genome.

Although chromosomal aberrations, copy number variants and de deleterious novo-mutations within protein coding genes have been associated with disorders, however for other disorders between 30% and 70% of the patients do not have a genetic diagnosis. A substantial proportion of those unexplained outcomes could be associated with damaging mutations within functional noncoding regions of the genomes associated with gene regulation (e.g. promoters, enhancers). Here we aim to apply a set of machine learning approaches to integrate public genomic, transcriptomic, epigenomic data from both patients and control individuals, to reconstruct tissue specific regulatory networks, annotate the noncoding functional elements involved in cardiac regulatory networks and characterise and prioritize variants disrupting those genomic elements.