Dissertation/Thesis Abstract

Computational design for analysis of SNP association studies
by Hsu, Chris, M.S., University of Southern California, 2008, 57; 1461689
Abstract (Summary)

SNP genotyping technology has advanced considerably in recent years, allowing for faster data generation at significantly lower cost. Investigators can now test a large number of SNPs across the human genome to locate putative risk alleles. Case-control study design, in particular, offers direct and unbiased estimation of disease risk. However, as the number of SNPs that can be genotyped continues to increase rapidly, the complexity and intensity of computation become important issues to consider. We offer a simple and automated approach to the computation of case-control genotype data especially of interest to users of the statistical analysis package SAS ®.

Indexing (document details)
Advisor: Stram, Daniel O.
Commitee: Haiman, Christopher, Setiawan, Veronica
School: University of Southern California
Department: Preventive Medicine (Health Behavior Research)
School Location: United States -- California
Source: MAI 47/04M, Masters Abstracts International
Source Type: DISSERTATION
Subjects: Biostatistics
Keywords: Genome wide, Logistic regression, SAS macro, SNP association
Publication Number: 1461689
ISBN: 9780549982623
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