Comparison of Statistical Methods of Haplotype Reconstruction and Logistic Regression for Association Studies

Karey Shumansky successfully defended her M.Sc. project entitled "Comparison of Statistical Methods of Haplotype Reconstruction and Logistic Regression for Association Studies" on 23 June 2005.

Can associations between diseases and genetic components of individuals be located?

Investigating association between disease and single nucleotide polymorphisms (SNPs) has been a popular approach for genetic association studies. More recently investigating association between disease and haplotypes has become another accepted method where haplotypes are physically linked combinations of alleles from a stretch of DNA and can serve to increase power of finding an association due to interactions between inclusive SNPs and the increased area of chromosome that is taken into consideration.

Determining haplotypes experimentally or by family studies is a costly and time-inefficient method, so haplotype reconstruction by statistical methods has become an adopted practice. The problem with computational methods is the extra source of error from ambiguous haplotypes has not been included in current statistical analyses. This paper investigates methods of error management with three different logistic regression packages, two of which are specific to analysis of genetic data. Methods are applied to simulated data and non-Hodgkin lymphoma data. This type of interdisciplinary work is a hallmark of our program in Applied Statistics at Simon Fraser University. For more information, please contact Karey Shumansky (etownbetty@yahoo.com) or her supervisors John Spinelli (jspinelli@bccancer.bc.ca) or Jinko Graham (jgraham@stat.sfu.ca), Department of Statistics and Actuarial Science, Simon Fraser University.

23 June 2005