This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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125
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Type:
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Contributed
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Date/Time:
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Monday, August 2, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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Abstract - #309161 |
Title:
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Detecting Gene-Gene Interactions with Survival Times Based on Generalized Multifactor Dimensionality Reduction Method
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Author(s):
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Seungyeoun Lee*+ and Min-Seok Kwon and Jaebong Lee and Taesung Park
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Companies:
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Sejong University and Seoul National University and Sejong University and Seoul National University
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Address:
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98 Gunja-dong, Kwangjin-gu, Seoul, 143-747, Republic of Korea
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Keywords:
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gene-gene interactions ;
multifactor dimensionality reduction method ;
survival time ;
Cox model ;
score residuals
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Abstract:
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Most statistical methods for genome-wide association studies (GWAS) have been based on identifying the genetic variants by locus-by-locus searching over all genotyped markers. However, there have been increasing empirical evidences for interaction effects between loci for complex disease in GWAS. One of approaches for identifying gene-gene interactions is the multifactor dimensionality reduction (MDR) method proposed by Ritchie et al. (2001). Recently Lou et al.(2007) proposed the generalized MDR (GMDR)), called the score-based MDR, in which the two distinct groups are defined by the score statistic. In this paper, we apply the GMDR to the survival time data in which the gene-gene interactions are considered adjusting the covariate effects such as age, sex and clinical variables. We analyze a real dataset of cancer patients and perform the simulation studies.
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