Study and comparison of next generation sequence algorithms and tools

dc.contributor.authorYates, Heath Landon
dc.date.accessioned2014-04-28T18:38:29Z
dc.date.available2014-04-28T18:38:29Z
dc.date.graduationmonthMayen_US
dc.date.issued2014-05-01
dc.date.published2014en_US
dc.description.abstractThis study is a comparison and exploration of next generation sequencing algorithms and tools. A simulation study was done to compare the performance of edgeR, DESeq, and baySeq in detecting differential gene expression. The methods were compared in context of a balanced pairwise design. The simulation results suggest that the methods are compa- rable under the conditions simulated. The study also explored real data comprised of one biological replicate between two treatments. Cufflinks and CummerRBund were used to detect differential gene expression. The visualization results from the real data suggest no differential expression is present.en_US
dc.description.advisorDoina Carageaen_US
dc.description.degreeMaster of Scienceen_US
dc.description.departmentDepartment of Computing and Information Sciencesen_US
dc.description.levelMastersen_US
dc.identifier.urihttp://hdl.handle.net/2097/17637
dc.language.isoenen_US
dc.publisherKansas State Universityen
dc.subjectNGSen_US
dc.subjectBaySeqen_US
dc.subjectEdgeRen_US
dc.subjectDESeqen_US
dc.subjectCufflinksen_US
dc.subject.umiComputer Science (0984)en_US
dc.titleStudy and comparison of next generation sequence algorithms and toolsen_US
dc.typeReporten_US

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