{"id":{"repo_id":"cape-town","oai_identifier":"oai:open.uct.ac.za:11427/4310"},"canonical_url":"https://search.dev.ndltd.org/etd/cape-town/oai:open.uct.ac.za:11427/4310","repository":{"repo_id":"cape-town","name":"University of Cape Town","base_url":"https://open.uct.ac.za/oai/request"},"display":{"title":"Genome-wide survey and analysis of allele-specific mRNA splicing in human and mouse","abstract":"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.","abstract_html":"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.","abstract_has_math":false,"creators":["Nembaware, Victoria Precious"],"institution":"Department of Molecular and Cell Biology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Seoighe, Cathal"],"committee_chairs":[],"committee_members":[],"year":2008,"date_issued":"2008","date_published":"2008","updated_at":"2026-07-22T22:23:24Z","subjects":[],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11427/4310","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Seoighe, Cathal"]},{"key":"dc:creator","label":"Author","values":["Nembaware, Victoria Precious"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-07-30T17:40:29Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-07-30T17:40:29Z"]},{"key":"dc:date.issued","label":"Date","values":["2008"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Department of Molecular and Cell Biology"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cape Town"]},{"key":"dc:type","label":"Dc Type","values":["Doctoral Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["PhD"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11427/4310"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Includes abstract.","Includes bibliographical references (leaves 125-145)."]},{"key":"dc:description.abstract","label":"Abstract","values":["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."]},{"key":"dc:title","label":"Title","values":["Genome-wide survey and analysis of allele-specific mRNA splicing in human and mouse"]}]}],"canonical_facts":{"dc:contributor.advisor":["Seoighe, Cathal"],"dc:creator":["Nembaware, Victoria Precious"],"dc:date.accessioned":["2014-07-30T17:40:29Z"],"dc:date.available":["2014-07-30T17:40:29Z"],"dc:date.issued":["2008"],"dc:description":["Includes abstract.","Includes bibliographical references (leaves 125-145)."],"dc:description.abstract":["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. 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