De Novo Sequence Assembly of Viral Quasispecies
| dc.contributor.author | Bristow, Franklin | |
| dc.contributor.examiningcommittee | Cameron, Helen (Computer Science) Ball, Blake (Medical Micriobiology) | en_US |
| dc.contributor.supervisor | Van Domselaar, Gary (Computer Science) Domaratzki, Michael (Computer Science) | en_US |
| dc.date.accessioned | 2012-10-23T21:21:45Z | |
| dc.date.available | 2012-10-23T21:21:45Z | |
| dc.date.issued | 2012-10-23 | |
| dc.degree.discipline | Computer Science | en_US |
| dc.degree.level | Master of Science (M.Sc.) | en_US |
| dc.description.abstract | The rapid replication and high mutation rates of viruses like HIV lead to the formation of a community of highly similar genomes, referred to as a viral quasispecies, in an infected individual. Next-generation sequencing technologies enable researchers to sequence a complete quasispecies community with reduced expense and effort compared to traditional sequencing methods. However, typical sequence assembly software is designed to reconstruct a single genome from sequencing reads rather than a community of highly similar genomes. We describe and implement a de novo assembly method for reconstructing variants from a quasispecies community using de Bruijn graphs and a novel, heuristic path-construction method designed to identify corresponding variations at long distances across the genome. We predict the relative abundance of reconstructed variants using an approach inspired from Markov chains. | en_US |
| dc.description.note | February 2013 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1993/9591 | |
| dc.language.iso | eng | en_US |
| dc.rights | open access | en_US |
| dc.subject | quasispecies | en_US |
| dc.subject | assembly | en_US |
| dc.title | De Novo Sequence Assembly of Viral Quasispecies | en_US |
| dc.type | master thesis | en_US |