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TESTING A METHODOLOGY FOR IDENTIFYING CLUSTERED ALLELE LOSS USING SNP ARRAY DATA

Zheng, Ping (2008) TESTING A METHODOLOGY FOR IDENTIFYING CLUSTERED ALLELE LOSS USING SNP ARRAY DATA. Master's Thesis, University of Pittsburgh. (Unpublished)

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Abstract

HumanHap550 Genotyping BeadChip provides a platform allowing for genotyping of single nucleotide polymorphisms (SNPs) greater than 550,000 loci. Such SNPs genotyping array technology makes it possible to identify genetic variation in individuals and across populations, profiling somatic mutations in cancer and loss of heterozygosity (LOH) events, amplifying deletions of regions of DNA, as well as possibly evaluating germline mutations in individuals. This study particularly focuses on analysis of clusters of Mendelian inconsistencies (MIs) in the SNPs array for six Russian radiation worker family trios, in order to identify the type of deletion variants for offspring such as inherited parental deletion variants (PDVs), spontaneous mutations (SMs) and germline mutations (GMs). By adapting the Bayesian theorem combining with the hereditary rule, this study presents an exciting result because 96.15% of genotypes in six selected clusters under the investigation could be identified as either PDVs or SMs/GMs, with two clusters are perfectly identified as SMs/GMs. This opens an avenue for further investigation of whether external environmental exposures (e.g., ionizing radiation) can effect the frequency of deletion variants (i.e., germline mutations) occurring in the offspring of highly exposed nuclear workers. While the applied methodology provides a practical means to recognize the genomic variations within the SNPs array some weaknesses of the study have been observed; particularly, the control group which consists of 112 individuals of Yoruba, Han Chinese, Japanese and Mormons is of deficiency on its sample size, diverse ethnicity and DNA process compared to the case group, and unclean potential hemizygous SNPs (i.e., Mendelian inconsistencies). Further statistical investigation and research needs to be conducted in order to overcome the weaknesses observed in the study; hence, the methodology introduced would be further of enhancement in its reliability and validity and it should be more effective when applied.Public health significance: The development of a reliable method to identify and count germline mutations in radiation workers could be generalized to exposures from any form of environmental mutagen (e.g., chemicals). Such a generalized marker could be used to measure the effects of various toxic environmental exposures on specific individuals and to predict genetically determined illness conditions.


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Zheng, Pingwangzp@comcast.net
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairDay, Richard Drdfac@pitt.eduRDFAC
Committee MemberGrant, Stephen Ggrantsg@upmc.edu
Committee MemberTseng, George Cctseng@pitt.eduCTSENG
Date: 31 January 2008
Date Type: Completion
Defense Date: 5 December 2007
Approval Date: 31 January 2008
Submission Date: 6 December 2007
Access Restriction: 5 year -- Restrict access to University of Pittsburgh for a period of 5 years.
Institution: University of Pittsburgh
Schools and Programs: Graduate School of Public Health > Biostatistics
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: Bayesian theorem; ionizing radiation; SNP array; germline mutations; allele loss; Mendelian inconsistencies; single nucleotide polymorphisms; statistical methodology
Other ID: http://etd.library.pitt.edu/ETD/available/etd-12062007-210615/, etd-12062007-210615
Date Deposited: 10 Nov 2011 20:08
Last Modified: 15 Nov 2016 13:53
URI: http://d-scholarship.pitt.edu/id/eprint/10111

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