Abstract
BackgroundOur goal was to identify subgroups of sib pairs from the Framingham Heart Study data set that provided higher evidence of linkage to particular candidate regions for cardiovascular disease traits. The focus of this method is not to claim identification of significant linkage to a particular locus but to show that tree models can be used to identify subgroups for use in selected sib-pair sampling schemes.ResultsWe report results using a novel recursive partitioning procedure to identify subgroups of sib pairs with increased evidence of linkage to systolic blood pressure and other cardiovascular disease-related quantitative traits, using the Framingham Heart Study data set provided by the Genetic Analysis Workshop 13. This procedure uses a splitting rule based on Haseman-Elston regression that recursively partitions sib-pair data into homogeneous subgroups.ConclusionsUsing this procedure, we identified a subgroup definition for use as a selected sib-pair sampling scheme. Using the characteristics that define the subgroup with higher evidence for linkage, we have identified an area of focus for further study.
Highlights
Our goal was to identify subgroups of sib pairs from the Framingham Heart Study data set that provided higher evidence of linkage to particular candidate regions for cardiovascular disease traits
BMC Genetics 2003, 4 http://www.biomedcentral.com/1471-2156/4/s1/S66 paper, we apply a recursive partitioning splitting rule developed by Shannon et al [4] to assess genetic linkage in the Framingham Heart Study (FHS) data set provided by the Genetic Analysis Workshop 13 (GAW13)
We are interested in augmenting sib-pair sampling by using this tree method to identify subgroups of sib pairs that show increased evidence of linkage of systolic blood pressure and other Cardiovascular disease (CVD)-related quantitative traits to compelling candidate regions identified in recent literature
Summary
Our goal was to identify subgroups of sib pairs from the Framingham Heart Study data set that provided higher evidence of linkage to particular candidate regions for cardiovascular disease traits. Cardiovascular disease (CVD) is a prime example of a complex disorder with numerous disease-related traits, determined by multiple genes and environmental factors, in which recursive partitioning can potentially aid in the detection and localization of the underlying genes. In this (page number not for citation purposes). We apply an alternative pruning rule to determine homogeneous subgroups of sibling pairs from the FHS data set that show stronger evidence of linkage to particular markers
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