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Development of a variant prioritisation algorithm for personalised medicine using an integrated service and research approach
Thesis (MSc)--Stellenbosch University, 2025.
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| Format: | Thesis |
| Language: | English |
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Stellenbosch : Stellenbosch University
2025
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| _version_ | 1867614082203385856 |
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| access_status_str | Open Access |
| author | Robertson, Duncan James |
| author2 | Kotze, Maritha |
| author_browse | Kotze, Maritha Robertson, Duncan James |
| author_facet | Kotze, Maritha Robertson, Duncan James |
| author_sort | Robertson, Duncan James |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MSc)--Stellenbosch University, 2025. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/132468 |
| institution | Stellenbosch University (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:46:22.874Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/132468 Development of a variant prioritisation algorithm for personalised medicine using an integrated service and research approach Robertson, Duncan James Kotze, Maritha Kinnear, Craig Tromp, Gerard Stellenbosch University. Faculty of Science. Centre for Bioinformatics & Computational Biology. Human genetics -- Variation Precision medicine -- Cancer Personalized medicine -- Data processing Whole genome/Exome sequencing -- Technique Genetic algorithms -- Testing Pharmacogenetics -- Testing UCTD Thesis (MSc)--Stellenbosch University, 2025. Robertson, D. J. 2025. Development of a Variant Prioritisation Algorithm for Personalised Medicine using an Integrated Service and Research approach. Unpublished masters thesis. Stellenbosch: Stellenbosch University [online]. Available: https://scholar.sun.ac.za/items/d4473a68-1ed4-48f4-aafd-6fe9ef8a7acc ENGLISH ABSTRACT: Background: Advances in next generation sequencing technology have enabled the incorporation of whole genome/exome sequencing (WGS/WES) into the care pathway of patients with non-communicable diseases (NCDs), such as cancer. First-tier point-of-care (PoC) genetic testing across various NCD pathways supports eligibility assessment and the interpretation of WGS/WES data. Pathology-supported genetic testing (PSGT) integrates these advances into clinical practice by ensuring that pathology results, family history and environmental factors guide the usage of genomic assays and their interpretation. To maximise the benefit to patients and society, PSGT applies personalised medicine through integrating service and research (PM-ISR) implemented in this study to improve the efficiency of filtering and prioritisation of the vast number of variants generated by WGS/WES. Aim: This study aims to construct an efficient, open-source pipeline for prioritising genetic variants called from WGS/WES data. The pipeline has been evaluated using data from a cohort of six cancer patients sequenced at the South African Medical Research Council Genomics Centre. Methods: A systematic literature review was conducted to determine the most appropriate bioinformatics tools for reducing the turn-around-time from WGS/WES data availability to patient report generation. By relying on the Variant Prioritisation Order Tool (VPOT) described in the literature for analysing Variant Call Format (VCF) files, the VCF-prioritise pipeline was developed using the Nextflow workflow management system. The results are presented in a spreadsheet format, divided into gene panels relevant to the pharmacodiagnostic profile of the patient cohort. The findings from the pipeline were evaluated for any additional or inconsistent findings compared to the previous genetic testing results available for each patient. Results: The VCF-prioritise pipeline enabled the processing of more than 4 million gene variants into a spreadsheet of results in less than 40 minutes, using only 16 threads and 8 GB of RAM. This approach is adaptable to multiple variant callers, sequencing technologies and reference sequences, and was successfully used to validate previous findings from the NCD PoC test kit and the WGS/WES results. Pharmacogenetic variants in the CYP2D6 gene previously detected with the NCD-pathways panel were missed in the WGS/WES data analysed in this study, likely due to problems with read alignment to the reference sequence. Additional variants relevant to an adverse warfarin drug response were uncovered in the WGS data of a patient experiencing severe drug side effects. Detection of a heterozygous EXO1: g.17406A>G variant confirmed by Sanger sequencing, supported previous findings indicating EXO1 as a novel breast cancer susceptibility locus for triple-negative breast cancer. Conclusion: The VCF-prioritise pipeline enables rapid return of WGS/WES research results by simplifying the variant prioritisation process. First-tier PoC genotyping added significant value during the pipeline validation phase, with cross-referencing of overlapping WGS/WES data proving crucial to prevent data mix-up. Implementation studies including sequence alignment and variant calling are warranted to further enhance the VCF-prioritise pipeline. Enhancements to support structural variant calling and SpliceAI scores could further improve the variant discovery rate. Lessons learned from this study will be applied to WGS testing of expanded cohorts in future. Masters 2025-06-09T10:32:14Z 2025-06-09T10:32:14Z 2025-03 Thesis https://scholar.sun.ac.za/handle/10019.1/132468 en Stellenbosch University xi, 77 pages : illustrations application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Human genetics -- Variation Precision medicine -- Cancer Personalized medicine -- Data processing Whole genome/Exome sequencing -- Technique Genetic algorithms -- Testing Pharmacogenetics -- Testing UCTD Robertson, Duncan James Development of a variant prioritisation algorithm for personalised medicine using an integrated service and research approach |
| title | Development of a variant prioritisation algorithm for personalised medicine using an integrated service and research approach |
| title_full | Development of a variant prioritisation algorithm for personalised medicine using an integrated service and research approach |
| title_fullStr | Development of a variant prioritisation algorithm for personalised medicine using an integrated service and research approach |
| title_full_unstemmed | Development of a variant prioritisation algorithm for personalised medicine using an integrated service and research approach |
| title_short | Development of a variant prioritisation algorithm for personalised medicine using an integrated service and research approach |
| title_sort | development of a variant prioritisation algorithm for personalised medicine using an integrated service and research approach |
| topic | Human genetics -- Variation Precision medicine -- Cancer Personalized medicine -- Data processing Whole genome/Exome sequencing -- Technique Genetic algorithms -- Testing Pharmacogenetics -- Testing UCTD |
| url | https://scholar.sun.ac.za/handle/10019.1/132468 |
| work_keys_str_mv | AT robertsonduncanjames developmentofavariantprioritisationalgorithmforpersonalisedmedicineusinganintegratedserviceandresearchapproach |