Abstract:
BACKGROUND:Because common complex diseases are affected by multiple genes and environmental factors, it is essential to investigate gene-gene and/or gene-environment interactions to understand genetic architecture of complex diseases. After the great success of large scale genome-wide association (GWA) studies using the high density single nucleotide polymorphism (SNP) chips, the study of gene-gene interaction becomes a next challenge. Multifactor dimensionality reduction (MDR) analysis has been widely used for the gene-gene interaction analysis. In practice, however, it is not easy to perform high order gene-gene interaction analyses via MDR in genome-wide level because it requires exploring a huge search space and suffers from a computational burden due to high dimensionality. RESULTS:We propose dimensional reduction analysis, Gene-MDR analysis for the fast and efficient high order gene-gene interaction analysis. The proposed Gene-MDR method is composed of two-step applications of MDR: within- and between-gene MDR analyses. First, within-gene MDR analysis summarizes each gene effect via MDR analysis by combining multiple SNPs from the same gene. Second, between-gene MDR analysis then performs interaction analysis using the summarized gene effects from within-gene MDR analysis. We apply the Gene-MDR method to bipolar disorder (BD) GWA data from Wellcome Trust Case Control Consortium (WTCCC). The results demonstrate that Gene-MDR is capable of detecting high order gene-gene interactions associated with BD. CONCLUSION:By reducing the dimension of genome-wide data from SNP level to gene level, Gene-MDR efficiently identifies high order gene-gene interactions. Therefore, Gene-MDR can provide the key to understand complex disease etiology.
journal_name
BMC Bioinformaticsjournal_title
BMC bioinformaticsauthors
Oh S,Lee J,Kwon MS,Weir B,Ha K,Park Tdoi
10.1186/1471-2105-13-S9-S5subject
Has Abstractpub_date
2012-06-11 00:00:00pages
S5issn
1471-2105pii
1471-2105-13-S9-S5journal_volume
13 Suppl 9pub_type
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