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On the hypothesis-free testing of metabolite ratios in genome-wide and metabolome-wide association studies

机译:在全基因组和代谢组学关联研究中无假设检验代谢物比率

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摘要

BackgroundGenome-wide association studies (GWAS) with metabolic traits and metabolome-wide association studies (MWAS) with traits of biomedical relevance are powerful tools to identify the contribution of genetic, environmental and lifestyle factors to the etiology of complex diseases. Hypothesis-free testing of ratios between all possible metabolite pairs in GWAS and MWAS has proven to be an innovative approach in the discovery of new biologically meaningful associations. The p-gain statistic was introduced as an ad-hoc measure to determine whether a ratio between two metabolite concentrations carries more information than the two corresponding metabolite concentrations alone. So far, only a rule of thumb was applied to determine the significance of the p-gain.
机译:背景技术具有代谢特征的全基因组关联研究(GWAS)和具有生物医学相关性特征的代谢组范围关联研究(MWAS)是确定遗传,环境和生活方式因素对复杂疾病病因的贡献的强大工具。 GWAS和MWAS中所有可能的代谢物对之间的比率的无假设测试已被证明是发现新的具有生物学意义的关联的一种创新方法。引入p增益统计信息作为临时度量,以确定两个代谢物浓度之间的比率是否比单独两个对应的代谢物浓度携带更多的信息。到目前为止,仅凭经验即可确定p增益的重要性。

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