On the hypothesis-free testing of metabolite ratios in genome-wide and metabolome-wide association studies.
On the hypothesis-free testing of metabolite ratios in genome-wide and metabolome-wide association studies.
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DOI：
10.1186/1471-2105-13-120
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发表时间：
2012-06-06
影响因子：
3
通讯作者：
Suhre K
中科院分区：
文献类型：
--
作者：
Petersen AK;Krumsiek J;Wägele B;Theis FJ;Wichmann HE;Gieger C;Suhre K
全基因组关联研究（GWAS）与代谢性状和代谢组关联研究（MWAS）与生物医学相关性的特征是强大的工具，以确定遗传，环境和生活方式因素的复杂疾病的病因学的贡献。GWAS和MWAS中所有可能的代谢物对之间的比率的无假设检验已被证明是发现新的生物学意义关联的创新方法。引入p-增益统计量作为一种特别测量，以确定两种代谢物浓度之间的比值是否比单独的两种相应代谢物浓度携带更多信息。到目前为止，仅应用经验法则来确定p增益的显著性。在这里，我们探索的p-增益的统计特性，通过模拟其密度和采样的实验数据。我们推导出代谢物对之间不同相关性水平的p-增益临界值，并表明B/（2*α）是p-增益的保守临界值，其中α是显著性水平，B是检测的代谢物对的数量。我们表明，p-增益是一个定义明确的措施，可用于确定统计学显着的代谢物比例在关联研究中，并提供了一个保守的显着性截止的p-增益用于未来的关联研究与代谢性状。
Genome-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. Here we explore the statistical properties of the p-gain through simulation of its density and by sampling of experimental data. We derive critical values of the p-gain for different levels of correlation between metabolite pairs and show that B/(2*α) is a conservative critical value for the p-gain, where α is the level of significance and B the number of tested metabolite pairs. We show that the p-gain is a well defined measure that can be used to identify statistically significant metabolite ratios in association studies and provide a conservative significance cut-off for the p-gain for use in future association studies with metabolic traits.
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影响因子：
3.7
作者：
Wang-Sattler, Rui;Yu, Yao;Mittelstrass, Kirstin;Lattka, Eva;Altmaier, Elisabeth;Gieger, Christian;Ladwig, Karl H.;Dahmen, Norbert;Weinberger, Klaus M.;Hao, Pei;Liu, Lei;Li, Yixue;Wichmann, H. -Erich;Adamski, Jerzy;Suhre, Karsten;Illig, Thomas
通讯作者：
Illig, Thomas
影响因子：
30.8
作者：
通讯作者：
--
影响因子：
3.7
作者：
Suhre K;Meisinger C;Döring A;Altmaier E;Belcredi P;Gieger C;Chang D;Milburn MV;Gall WE;Weinberger KM;Mewes HW;Hrabé de Angelis M;Wichmann HE;Kronenberg F;Adamski J;Illig T
通讯作者：
Illig T
影响因子：
4.8
作者：
Altmaier, Elisabeth;Ramsay, Steven L.;Suhre, Karsten
通讯作者：
Suhre, Karsten
影响因子：
--
作者：
Suhre, Karsten;Roemisch-Margl, Werner;Augustin, Robert
通讯作者：
Augustin, Robert