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.graduationmonthMay
dc.date.issued2014-05-01
dc.date.published2014
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.
dc.description.advisorDoina Caragea
dc.description.degreeMaster of Science
dc.description.departmentDepartment of Computing and Information Sciences
dc.description.levelMasters
dc.identifier.urihttp://hdl.handle.net/2097/17637
dc.language.isoen
dc.publisherKansas State University
dc.rights© the author. This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectNGS
dc.subjectBaySeq
dc.subjectEdgeR
dc.subjectDESeq
dc.subjectCufflinks
dc.subject.umiComputer Science (0984)
dc.titleStudy and comparison of next generation sequence algorithms and tools
dc.typeReport

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