Evaluating the Application of Allele Frequency in the Saudi Population Variant Detection
dc.contributor.advisor | Hoehndorf, Robert | |
dc.contributor.author | Alsaedi, Sakhaa | |
dc.date.accessioned | 2020-04-26T12:15:42Z | |
dc.date.available | 2020-04-26T12:15:42Z | |
dc.date.issued | 2020-04-26 | |
dc.identifier.citation | Alsaedi, S. (2020). Evaluating the Application of Allele Frequency in the Saudi Population Variant Detection. KAUST Research Repository. https://doi.org/10.25781/KAUST-7K6DI | |
dc.identifier.doi | 10.25781/KAUST-7K6DI | |
dc.identifier.uri | http://hdl.handle.net/10754/662641 | |
dc.description.abstract | Human Mendelian disease in Saudi Arabia is both significant and challenging. Next-generation sequencing (NGS) has resulted in important discoveries of the genetic variants responsible for inherited disease. However, the success of clinical genomics using NGS requires accurate and consistent identification of rare genome variants. Rarity is one very important criterion for pathogenicity. Here we describe a model to detect variants by analyzing allele frequencies of a Saudi population. This work will enhance the opportunity to improve variant calling workflow to gain robust frequency estimates in order to better detect rare and unusual variants which are frequently associated with inherited disease. | |
dc.language.iso | en | |
dc.subject | variants | |
dc.subject | variant calling | |
dc.subject | saudi genome | |
dc.subject | population | |
dc.subject | mendelians diseases | |
dc.subject | allele frequency | |
dc.title | Evaluating the Application of Allele Frequency in the Saudi Population Variant Detection | |
dc.type | Thesis | |
dc.contributor.department | Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division | |
dc.rights.embargodate | 2021-04-20 | |
thesis.degree.grantor | King Abdullah University of Science and Technology | |
dc.contributor.committeemember | Gao, Xin | |
dc.contributor.committeemember | Gojobori, Takashi | |
thesis.degree.discipline | Computer Science | |
thesis.degree.name | Master of Science | |
dc.rights.accessrights | At the time of archiving, the student author of this thesis opted to temporarily restrict access to it. The full text of this thesis will become available to the public after the expiration of the embargo on 2021-04-20. | |
refterms.dateFOA | 2020-04-26T12:15:44Z | |
kaust.request.doi | yes |
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