Includes abstract. / Includes bibliographical references (leaves 125-145). / This dissertation aims to examine allele-specific splicing in human and mouse using publicly available datasets. Such datasets, which have been generated from multiple tissue sources and from individuals of diverse backgrounds, are rich and cheap reservoirs of transcript isoforms resulting from alternative splicing as well as isoforms resulting from mutations or polymorphisms (allele-specific isoforms). Published tools were used to analyse microarray and genomic data. However, for the assessment of allele-specific splicing using publicly available high-throughput transcript sequences, we present two novel methods: a heuristic method for quantifying the prevalence of allele-specific splicing and a more sophisticated maximum likelihood method for the detection of individual examples of allele-specific splicing. These methods make use of transcripts that can be mapped to both polymorphisms and computationally predicted mRNA isoforms. Inference of polymorphic alleles from transcripts is laborious hence a pre-computed database was created for the human data and made publicly available for use by the wider research community.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/4310 |
| Date | January 2008 |
| Creators | Nembaware, Victoria Precious |
| Contributors | Seoighe, Cathal |
| Publisher | University of Cape Town, Faculty of Science, Department of Molecular and Cell Biology |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Doctoral Thesis, Doctoral, PhD |
| Format | application/pdf |
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