Worcester Polytechnic Institute Electronic Theses and Dissertations Collection

Title page for ETD etd-0502101-104844


Document Typethesis
Author NamePungliya, Manish S
URNetd-0502101-104844
TitleSingle nucleotide polymorphism analysis in application to fine gene mapping
DegreeMS
DepartmentBiology & Biotechnology
Advisors
  • Dr. Julia Krushkal, Advisor
  • Dr. Elizabeth Ryder, Co-Advisor
  • Dr. Carolina Ruiz, Thesis Committee
  • Dr. David Adams, Committee Member
  • Dr. Ronald Cheetham, Department Head
  • Keywords
  • SNP
  • Single nucleotide polymorphism
  • linkage disequilibrium
  • transition
  • transversion
  • Date of Presentation/Defense2001-04-17
    Availability unrestricted

    Abstract

    Single nucleotide polymorphisms (SNPs) are single base variations among groups of individuals. In order to study their properties in fine gene mapping, I considered their occurrence as transitions and transversions. The aim of the study was to classify each polymorphism depending upon whether it was a transition or transversion and to calculate the proportions of transitions and transversions in the SNP data from the public databases. This ratio was found to be 2.35 for data from the Whitehead Institute for Genome Research database, 2.003 from the Genome Database, and 2.086 from the SNP Consortium database. These results indicate that the ratio of the numbers of transitions to transversions was very different than the expected ratio of 0.5. To study the effect of different transition to transversion ratios in fine gene mapping, a simulation study was performed to generate nucleotide sequence data. The study investigated the effect of different transition to transversion ratios on linkage disequilibrium parameter (LD), which is frequently used in association analysis to identify functional mutations. My results showed no considerable effect of different transition to transversion ratios on LD. I also studied the distribution of allele frequencies of biallelic SNPs from the Genome Database. My results showed that the most common SNPs are normally distributed with mean allele frequency of 0.7520 and standard deviation of 0.1272. These results can be useful in future studies for simulating SNP behavior. I also studied the simulated data provided by the Genetic Analysis Workshop 12 to identify functional SNPs in candidate genes by using the genotype-specific linkage disequilibrium method.

    Files
  • pungilya.pdf

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