Understanding and Improving Identification of Somatic Variants
It 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 iden...
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ndltd-VTETD-oai-vtechworks.lib.vt.edu-10919-729692020-11-25T05:37:30Z Understanding and Improving Identification of Somatic Variants Vijayan, Vinaya Animal and Poultry Sciences Zhang, Liqing Wu, Xiaowei Heath, Lenwood S. Franck, Christopher T. Somatic variants Somatic variant callers Somatic point mutations Short tandem repeat variation Lung squamous cell carcinoma It 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. Ph. D. 2016-09-21T08:00:51Z 2016-09-21T08:00:51Z 2016-09-20 Dissertation vt_gsexam:8848 http://hdl.handle.net/10919/72969 In Copyright http://rightsstatements.org/vocab/InC/1.0/ ETD application/pdf Virginia Tech |
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Somatic variants Somatic variant callers Somatic point mutations Short tandem repeat variation Lung squamous cell carcinoma |
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Somatic variants Somatic variant callers Somatic point mutations Short tandem repeat variation Lung squamous cell carcinoma Vijayan, Vinaya Understanding and Improving Identification of Somatic Variants |
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It 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. === Ph. D. |
author2 |
Animal and Poultry Sciences |
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Animal and Poultry Sciences Vijayan, Vinaya |
author |
Vijayan, Vinaya |
author_sort |
Vijayan, Vinaya |
title |
Understanding and Improving Identification of Somatic Variants |
title_short |
Understanding and Improving Identification of Somatic Variants |
title_full |
Understanding and Improving Identification of Somatic Variants |
title_fullStr |
Understanding and Improving Identification of Somatic Variants |
title_full_unstemmed |
Understanding and Improving Identification of Somatic Variants |
title_sort |
understanding and improving identification of somatic variants |
publisher |
Virginia Tech |
publishDate |
2016 |
url |
http://hdl.handle.net/10919/72969 |
work_keys_str_mv |
AT vijayanvinaya understandingandimprovingidentificationofsomaticvariants |
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