Environmental factor dependent maximum likelihood method for association study targeted to personalized medicine.

T Tsunoda; R Yamada; T Tanaka; Y Ohnishi; N Kamatani

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PubMed · 11700591

Environmental factor dependent maximum likelihood method for association study targeted to personalized medicine.

T Tsunoda·R Yamada·T Tanaka·Y Ohnishi·N Kamatani

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Abstract

The most challenging strategy for analyzing genome-wide polymorphisms and/or expression profiles is to solve multi-factor causal-relationship simultaneously. As the first step, we propose a framework of association study using maximum likelihood method that simultaneously handles genetic polymorphisms and epi-genetic information, e.g. environmental factors. We evaluate the theory by applying it to genotyped data of myocardial infarction (MI) patients.

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Algorithms Case-Control Studies Computational Biology Environment Female Gene Expression Profiling Genotype Humans Likelihood Functions Male Models, Genetic Myocardial Infarction Phenotype Polymorphism, Genetic Polymorphism, Single Nucleotide Risk Factors Journal Article

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T Tsunoda, R Yamada, T Tanaka, Y Ohnishi, N Kamatani. 2000. Environmental factor dependent maximum likelihood method for association study targeted to personalized medicine.. https://pubmed.ncbi.nlm.nih.gov/11700591/

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