Abstract
In this paper we test for association between copy number variation and diabetes in a subset of individuals from the Framingham Heart Study. We used the 500 k SNP data and called copy number variation using two algorithms: the genome alteration detection algorithm of Pique-Regi et al. and the software Golden Helix. We then tested for association between copy number and diabetes using a gene-based analysis. Our results show little evidence of association between copy number and diabetes status. Furthermore, our results indicate a relatively poor level of agreement between copy number calls resulting from the two programs. We then examined potential causes for this difference in results and the implications for future studies.
Highlights
One of the most important challenges facing the field of biology today is making sense of genetic variation
In this paper we implement population-based tests for association between copy number variation (CNV) and phenotypic variation within the Framingham Heart Study samples provided as part of Genetic Analysis Workshop 16 Problem 2
In order to protect against undiagnosed diabetes, we insisted that cases had a fasting plasma glucose measure of at least 126 mg/dl, while controls had a fasting measure less than 110 mg/ dl
Summary
One of the most important challenges facing the field of biology today is making sense of genetic variation. One form of variation that is gaining an increasing level of attention is copy number variation (CNV). The term CNV is used to encompass a variety of polymorphisms that occur at the sequence level and that affect the copy number of regions of genetic material. While a number of associations between single-nucleotide polymorphisms (SNPs) and disease have been verified, it remains the case that the effect sizes of these polymorphisms appear relatively small, with reported odds ratios typically being below 1.5 (see Estivill and Armengol [3] for a recent review). In this paper we implement population-based tests for association between CNV and phenotypic variation within the Framingham Heart Study samples provided as part of Genetic Analysis Workshop 16 Problem 2
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