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A topic model based approach to inferring episodic directional selection in protein coding sequences
Pathogens, such as HIV and influenza, evolve in response to the selective pressures of their host environments accumulating changes in their genomes that offer fitness benefits. This selective pressure is characterised by three properties: (1.) it is episodic, tracking changes in the adaptive immune...
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| Format: | Thesis |
| Language: | English |
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Department of Statistical Sciences
2016
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| _version_ | 1867613338969571328 |
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| access_status_str | Open Access |
| author | Sadiq, Hassan Taiwo |
| author2 | Lacerda, Miguel |
| author_browse | Lacerda, Miguel Sadiq, Hassan Taiwo |
| author_facet | Lacerda, Miguel Sadiq, Hassan Taiwo |
| author_sort | Sadiq, Hassan Taiwo |
| collection | Thesis |
| description | Pathogens, such as HIV and influenza, evolve in response to the selective pressures of their host environments accumulating changes in their genomes that offer fitness benefits. This selective pressure is characterised by three properties: (1.) it is episodic, tracking changes in the adaptive immune response and drug therapy, (2.) it is directional in that only particular amino acid substitutions are favoured and (3.) it varies between genomic loci. Most previous models have ignored or inadequately addressed some of these phenomena. This work extends recent approaches to modelling episodic directional selection acting on protein-coding sequences. We use inference techniques within the topic model framework to identify loci evolving under natural selection. A notable example of such techniques are the variational Bayesian methods. We show that our approach performs well in terms of specificity and power, and demonstrate its utility by applying it to some real datasets of HIV sequences. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/20013 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:34:33.896Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2016 |
| publishDateRange | 2016 |
| publishDateSort | 2016 |
| publisher | Department of Statistical Sciences |
| publisherStr | Department of Statistical Sciences |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/20013 A topic model based approach to inferring episodic directional selection in protein coding sequences Sadiq, Hassan Taiwo Lacerda, Miguel Decision Sciences and Analytics Pathogens, such as HIV and influenza, evolve in response to the selective pressures of their host environments accumulating changes in their genomes that offer fitness benefits. This selective pressure is characterised by three properties: (1.) it is episodic, tracking changes in the adaptive immune response and drug therapy, (2.) it is directional in that only particular amino acid substitutions are favoured and (3.) it varies between genomic loci. Most previous models have ignored or inadequately addressed some of these phenomena. This work extends recent approaches to modelling episodic directional selection acting on protein-coding sequences. We use inference techniques within the topic model framework to identify loci evolving under natural selection. A notable example of such techniques are the variational Bayesian methods. We show that our approach performs well in terms of specificity and power, and demonstrate its utility by applying it to some real datasets of HIV sequences. 2016-06-10T10:53:55Z 2016-06-10T10:53:55Z 2015 Master Thesis Masters MSc http://hdl.handle.net/11427/20013 eng application/pdf Department of Statistical Sciences Faculty of Science University of Cape Town |
| spellingShingle | Decision Sciences and Analytics Sadiq, Hassan Taiwo A topic model based approach to inferring episodic directional selection in protein coding sequences |
| thesis_degree_str | Master's |
| title | A topic model based approach to inferring episodic directional selection in protein coding sequences |
| title_full | A topic model based approach to inferring episodic directional selection in protein coding sequences |
| title_fullStr | A topic model based approach to inferring episodic directional selection in protein coding sequences |
| title_full_unstemmed | A topic model based approach to inferring episodic directional selection in protein coding sequences |
| title_short | A topic model based approach to inferring episodic directional selection in protein coding sequences |
| title_sort | topic model based approach to inferring episodic directional selection in protein coding sequences |
| topic | Decision Sciences and Analytics |
| url | http://hdl.handle.net/11427/20013 |
| work_keys_str_mv | AT sadiqhassantaiwo atopicmodelbasedapproachtoinferringepisodicdirectionalselectioninproteincodingsequences AT sadiqhassantaiwo topicmodelbasedapproachtoinferringepisodicdirectionalselectioninproteincodingsequences |