TY - GEN
T1 - A novel information theoretic method for detecting gene-gene and gene-environment interactions in complex diseases
AU - Chanda, Pritam
AU - Zhang, Aidong
AU - Ramanthan, Murali
PY - 2008
Y1 - 2008
N2 - Gene-gene and gene-environment interactions play important roles in the etiology of complex multi-factorial diseases. With the advancements in genotyping technology, large genetic association studies based on hundreds of thousands of single-nucleotide polymorphisms are a popular option for the study of complex diseases. In this paper we use information theoretic concepts to develop a novel method for detecting statistical gene-gene and gene-environment interactions in complex disease models. We explore the effectiveness of our method with extensive simulations using different gene-gene interaction models and the rheumatoid arthritis dataset from Genetic Analysis Workshop-15. The performance of the method was compared to the well known multi-factor dimensionality reduction (MDR) and generalized MDR (GMDR) methods. We demonstrate that our method is capable of analyzing a diverse range of epidemiological data sets containing evidences for gene- gene interactions.
AB - Gene-gene and gene-environment interactions play important roles in the etiology of complex multi-factorial diseases. With the advancements in genotyping technology, large genetic association studies based on hundreds of thousands of single-nucleotide polymorphisms are a popular option for the study of complex diseases. In this paper we use information theoretic concepts to develop a novel method for detecting statistical gene-gene and gene-environment interactions in complex disease models. We explore the effectiveness of our method with extensive simulations using different gene-gene interaction models and the rheumatoid arthritis dataset from Genetic Analysis Workshop-15. The performance of the method was compared to the well known multi-factor dimensionality reduction (MDR) and generalized MDR (GMDR) methods. We demonstrate that our method is capable of analyzing a diverse range of epidemiological data sets containing evidences for gene- gene interactions.
UR - https://www.scopus.com/pages/publications/67649125114
U2 - 10.1109/BIBE.2008.4696677
DO - 10.1109/BIBE.2008.4696677
M3 - Conference contribution
AN - SCOPUS:67649125114
SN - 9781424428458
T3 - 8th IEEE International Conference on BioInformatics and BioEngineering, BIBE 2008
BT - 8th IEEE International Conference on BioInformatics and BioEngineering, BIBE 2008
T2 - 8th IEEE International Conference on BioInformatics and BioEngineering, BIBE 2008
Y2 - 8 October 2008 through 10 October 2008
ER -