VSIM: Visualization and Simulation of Genomes for Premarital Testing

Overview

Abstract

Interpretation and simulation of the large-scale genomics data are very challenging, and currently, many web tools have been developed to analyze genomic variation which supports automated visualization of a variety of high throughput genomics data. We have developed VSIM an automated and easy to use web application for interpretation and visualization of a variety of genomics data, it identifies the candidate disease variants by referencing to four databases Clinvar, GWAS, DIDA, and PharmGKB, and predicted the pathogenic variants. Moreover, it investigates the attitude towards premarital genetic screening by simulating a population of children and analyze the diseases they might be carrying, based on the genetic factors of their parents taking into consideration the recombination hotspots. VSIM supports output formats based on Ideograms that are easy to interpret and understand, which makes it a biologist-friendly powerful tool for data visualization, and interpretation of personal genomic data. Our results show that VSIM can efficiently identify the causative variants by referencing well-known databases for variants in whole genomes associated with different kinds of diseases. Moreover, it can be used for premarital genetic screening by simulating a population of children and analyze the disorder they might be carrying. The output format provides a better understanding of such large genomics data. VSIM thus helps biologists and marriage counselors to visualize a variety of genomic variants associated with diseases seamlessly.

Brief Biography

Azza Althagafi joined KAUST in 2016 as a Master Student in Computer Science. She was a teaching assistant at Taif University, Taif, Saudi Arabia. Currently, she is a Ms/Ph.D. at the Bio-Ontology Research Group (BORG) at KAUST. Her research interests are bioinformatics, machine learning, artificial intelligence, analysis of genomic data, and biomedical applications. Her thesis work focuses on the simulation and interpretation of human genomes for pre-marital testing.