Germline genetic contribution to metabolic pathways in cancer

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dc.contributor.authorJalilkhany, Mansoureh
dc.contributor.supervisorNumanagić, Ibrahim
dc.contributor.supervisorLum, Julian J.
dc.date.accessioned2022-12-21T19:24:01Z
dc.date.available2022-12-21T19:24:01Z
dc.date.copyright2022en_US
dc.date.issued2022-12-21
dc.degree.departmentDepartment of Computer Science
dc.degree.levelMaster of Applied Science M.A.Sc.en_US
dc.description.abstractCancer research is essential in improving cancer prevention, detection, and treatment. The analysis of cancer genomes helps uncover gene abnormalities that cause the emergence and spread of many types of cancer. While many studies have investigated various landscapes of cancer, the role of inherited genetic mutations is primarily unexplored. In this work, we studied the genetic variations affecting metabolic pathways in cancer from the SNP-level, gene-level, and pathway-level aspects. First, we identified the significant SNPs and genes associated with metabolic traits. Then we introduced A-LAVA to perform gene set analysis and detect the most significant gene sets associated with the target traits. A-LAVA is a competitive gene set analysis approach that resolves the bias resulting from overlapping gene sets, as a potential confounding effect, in addition to other standard corrections performed in current methods. We also showed that accounting for the shared genes present in the gene sets is essential for any gene set analysis approach when there is an overlap between gene sets, as it remarkably affects the results.en_US
dc.description.scholarlevelGraduateen_US
dc.identifier.urihttp://hdl.handle.net/1828/14578
dc.languageEnglisheng
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.subjectGWASen_US
dc.subjectGermline genetic mutationsen_US
dc.subjectgene-set analysisen_US
dc.subjectInherited SNPsen_US
dc.subjectCanceren_US
dc.subjectMetabolic pathways in canceren_US
dc.subjectmetabolic traiten_US
dc.subjectInherited mutated genesen_US
dc.titleGermline genetic contribution to metabolic pathways in canceren_US
dc.typeThesisen_US

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