Dissertation/ Thesis
Assessing the discoverability of variant proteins causing rare forms of paediatric diabetes using proteogenomics
| Title: | Assessing the discoverability of variant proteins causing rare forms of paediatric diabetes using proteogenomics |
|---|---|
| Authors: | Naidoo, Lorensha |
| Contributors: | Patterton, Hugh-George, Vaudel, Marc, Stellenbosch University. Faculty of Science. Centre for Bioinformatics & Computational Biology. |
| Publisher Information: | Stellenbosch University |
| Publication Year: | 2025 |
| Collection: | Stellenbosch University: SUNScholar Research Repository |
| Subject Terms: | Diabetes in children -- Genetic aspects, Proteomics -- Data processing, Proteins -- Analysis, Peptides -- Analysis, Spectrum analysis -- Data processing, Machine learning -- Computer simulation, Bayesian statistical decision theory -- Computer simulation, UCTD |
| Description: | Thesis (MSc)--Stellenbosch University, 2025. ; Naidoo, L. 2025. Assessing the discoverability of variant proteins causing rare forms of paediatric diabetes using proteogenomics. Unpublished masters thesis. Stellenbosch: Stellenbosch University [online]. Available: https://scholar.sun.ac.za/items/fa2ce23c-42d1-4183-b3ba-b969d378e482 ; ENGLISH ABSTRACT: Monogenic diabetes is a rare form of paediatric diabetes caused by a pathogenic variant occurring in a single gene associated with insulin production from pancreatic β-cells, resulting in hyperglycaemic complications. Maturity-onset diabetes of the young (MODY) is a subtype of monogenic diabetes, accounting for 2 – 5% of diabetic cases. Patient classification has revealed undiagnosed symptomatic cohorts speculated to result from unknown genetic variants. Identifying these variants is essential for advancing precision medicine and providing specialised medical care. Proteogenomics allows for the identification of alternative forms of proteins resulting from genomic variation. Protein samples are processed using mass spectrometry to obtain peptide sequences that are then annotated to a sequence database using search engines, e.g. SEQUEST and X!Tandem. Peptide-spectrum matches (PSMs) with varying confidence scores are produced; however, there is no clear distinction between correct and incorrect PSMs. Additionally, distinguishing variant PSMs from canonical PSMs remains challenging due to their low frequency and sequence similarity. The target-decoy approach (TDA) is a common method for classifying correct and incorrect PSMs and is used in existing PSM processing tools, such as Percolator. Target sequences are peptide sequences from proteomic databases, while decoy sequences are artificially generated to serve as a null model for error rate estimation. To the knowledge of this work, the TDA has not been implemented towards improving the discrimination performance of variant PSMs. To this end, this study conducts an exploratory analysis to improve the classification of ... |
| Document Type: | thesis |
| File Description: | xiv, 143 pages : illustrations; application/pdf |
| Language: | unknown |
| Relation: | https://scholar.sun.ac.za/handle/10019.1/134730 |
| Availability: | https://scholar.sun.ac.za/handle/10019.1/134730 |
| Rights: | Stellenbosch University |
| Accession Number: | edsbas.CDF890BC |
| Database: | BASE |
Be the first to leave a comment!