Data-driven integration of epidemiological and toxicological data to select candidate interacting genes and environmental factors in association with disease.
Data-driven integration of epidemiological and toxicological data to select candidate interacting genes and environmental factors in association with disease.
复制标题
流行病学和毒理学数据的数据驱动整合，以选择与疾病相关的候选相互作用基因和环境因素。
DOI：
10.1093/bioinformatics/bts229
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
Butte,AtulJ
中科院分区：
文献类型：
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作者：
Patel,ChiragJ;Chen,Rong;Butte,AtulJ
Motivation:Complex diseases, such as Type 2 Diabetes Mellitus (T2D), result from the interplay of both environmental and genetic factors. However, most studies investigate either the genetics or the environment and there are a few that study their possible interaction in context of disease. One key challenge in documenting interactions between genes and environment includes choosing which of each to test jointly. Here, we attempt to address this challenge through a data-driven integration of epidemiological and toxicological studies. Specifically, we derive lists of candidate interacting genetic and environmental factors by integrating findings from genome-wide and environment-wide association studies. Next, we search for evidence of toxicological relationships between these genetic and environmental factors that may have an etiological role in the disease. We illustrate our method by selecting candidate interacting factors for T2D.Contact:abutte@stanford.edu
