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dc.contributor.authorVijayan, Vinayaen_US
dc.date.accessioned2016-09-21T08:00:51Z
dc.date.available2016-09-21T08:00:51Z
dc.date.issued2016-09-20en_US
dc.identifier.othervt_gsexam:8848en_US
dc.identifier.urihttp://hdl.handle.net/10919/72969
dc.description.abstractIt is important to understand the entire spectrum of somatic variants to gain more insight into mutations that occur in different cancers for development of better diagnostic, prognostic and therapeutic tools. This thesis outlines our work in understanding somatic variant calling, improving the identification of somatic variants from whole genome and whole exome platforms and identification of biomarkers for lung cancer. Integrating somatic variants from whole genome and whole exome platforms poses a challenge as variants identified in the exonic regions of the whole genome platform may not be identified on the whole exome platform and vice-versa. Taking a simple union or intersection of the somatic variants from both platforms would lead to inclusion of many false positives (through union) and exclusion of many true variants (through intersection). We develop the first framework to improve the identification of somatic variants on whole genome and exome platforms using a machine learning approach by combining the results from two popular somatic variant callers. Testing on simulated and real data sets shows that our framework identifies variants more accurately than using only one somatic variant caller or using variants from only one platform. Short tandem repeats (STRs) are repetitive units of 2-6 nucleotides. STRs make up approximately 1% of the human genome and have been traditionally used as genetic markers in population studies. We conduct a series of in silico analyses using the exome data of 32 individuals with lung cancer to identify 103 STRs that could potentially serve as cancer diagnostic markers and 624 STRs that could potentially serve as cancer predisposition markers. Overall these studies improve the accuracy in identification of somatic variants and highlight the association of STRs to lung cancer.en_US
dc.format.mediumETDen_US
dc.publisherVirginia Techen_US
dc.rightsThis Item is protected by copyright and/or related rights. Some uses of this Item may be deemed fair and permitted by law even without permission from the rights holder(s), or the rights holder(s) may have licensed the work for use under certain conditions. For other uses you need to obtain permission from the rights holder(s).en_US
dc.subjectSomatic variantsen_US
dc.subjectSomatic variant callersen_US
dc.subjectSomatic point mutationsen_US
dc.subjectShort tandem repeat variationen_US
dc.subjectLung squamous cell carcinomaen_US
dc.titleUnderstanding and Improving Identification of Somatic Variantsen_US
dc.typeDissertationen_US
dc.contributor.departmentAnimal and Poultry Sciencesen_US
dc.description.degreePh. D.en_US
thesis.degree.namePh. D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineGenetics, Bioinformatics, and Computational Biologyen_US
dc.contributor.committeechairZhang, Liqingen_US
dc.contributor.committeememberWu, Xiaoweien_US
dc.contributor.committeememberHeath, Lenwood S.en_US
dc.contributor.committeememberFranck, Christopher Thomasen_US


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