Angel: Towards a Multi-level Method for the Analysis of Variants in Individual Genomes

Abstract

Genomic medicine pursues to develop methods for improving early diagnosis processes, the efficiency of treatments and facilitating the discovery of new therapies, and mainly searches for associations between the genotype of individuals and their phenotypical features. The huge genomic variability is a major difficulty for developing effective computational methods, since the correlation of a locus and a phenotype does not necessarily mean causality. Hence, methods for genome-based diagnosis need to take into account the complexity of the genomic background and the biological networks involved in the manifestation of phenotypes and disorders.

We describe a method for analysing the variants identified in the genome of human individuals, sequenced using Next-Generation Sequencing techniques, and such analysis is based on the existing knowledge about the genes, pathways and phenotypes. This method is capable of generating quantitative scores at the levels of gene, pathway and phenotype, which represent the degree of functional disorder of the corresponding gene or pathway, and the level of contribution to development of a specific phenotype of the genomic variant. The validation experiments performed with exomes of patients with “Congenital Disorder of Glycosylation, Type IA” (CDG1A) have shown positive results.