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 diseases 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 kind of diseases. Moreover, it can be used for premarital genetic screening by simulating a population of offspring and analyze the disorders they might be carrying. The output format provides a better understanding of such large genomics data. VSIM thus helps biologists and marriage counsellor to visualize a variety of genomic variants associated with diseases seamlessly.
| Identifer | oai:union.ndltd.org:kaust.edu.sa/oai:repository.kaust.edu.sa:10754/630088 |
| Date | 28 November 2018 |
| Creators | Althagafi, Azza Th. |
| Contributors | Hoehndorf, Robert, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, Moshkov, Mikhail, Gojobori, Takashi |
| Source Sets | King Abdullah University of Science and Technology |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Rights | 2019-11-28, At the time of archiving, the student author of this thesis opted to temporarily restrict access to it. The full text of this thesis became available to the public after the expiration of the embargo on 2019-11-28. |
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