Use of tree-based models to identify subgroups and increase power to detect linkage to cardiovascular disease traits

Description:

This article discusses the use of tree-based models to identify subgroups and increase power to detect linkage to cardiovascular disease traits.

Creator(s):
Creation Date: December 31, 2003
Partner(s):
UNT College of Arts and Sciences
Collection(s):
UNT Scholarly Works
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Creator (Author):
Costello, Tracy Jennifer

University of Texas MD Anderson Cancer Center; University of Texas Health Science Center

Creator (Author):
Swartz, Michael D.

University of Texas MD Anderson Cancer Center; Rice University

Creator (Author):
Sabripour, Mahyar

University of Texas MD Anderson Cancer Center; University of Texas Health Science Center

Creator (Author):
Gu, Xiangjun

University of Texas MD Anderson Cancer Center

Creator (Author):
Sharma, Rishika

University of North Texas

Creator (Author):
Etzel, Carol J.

University of Texas MD Anderson Cancer Center

Publisher Info:
Publisher Name: BioMed Central
Place of Publication: [London, United Kingdom]
Date(s):
  • Creation: December 31, 2003
Description:

This article discusses the use of tree-based models to identify subgroups and increase power to detect linkage to cardiovascular disease traits.

Degree:
Note:

Background: The authors' 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. Results: The authors 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. Conclusions: Using this procedure, the authors 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, the authors have identified an area of focus for further study.

Physical Description:

6 p.

Language(s):
Subject(s):
Keyword(s): cardiovascular diseases | Framingham Heart Study | tree-based models
Source: Genetic Analysis Workshop 13: Analysis of Longitudinal Family Data for Complex Diseases and Related Risk Factors, 2002, New Orleans, Louisiana, United States
Partner:
UNT College of Arts and Sciences
Collection:
UNT Scholarly Works
Identifier:
  • DOI: 10.1186/1471-2156-4-S1-S66 |
  • ARK: ark:/67531/metadc122143
Resource Type: Article
Format: Text
Rights:
Access: Public
Citation:
Publication Title: BMC Genetics
Volume: 4
Edition: Suppl I
Peer Reviewed: Yes