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Imaging Genetics: Bio-Informatics and Bio-Statistics Challenges

机译:成像遗传学:生物信息学与生物统计学挑战

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The IMAGEN study—a very large European Research Project—seeks to identify and characterize biological and environmental factors that influence teenagers mental health. To this aim, the consortium plans to collect data for more than 2000 subjects at 8 neuroimaging centres. These data comprise neuroimaging data, behavioral tests (for up to 5 hours of testing), and also white blood samples which are collected and processed to obtain 650 k single nucleotide polymorphisms (SNP) per subject. Data for more than 1000 subjects have already been collected. We describe the statistical aspects of these data and the challenges, such as the multiple comparison problem, created by such a large imaging genetics study (i.e., 650 k for the SNP, 50 k data per neuroimage).We also suggest possible strategies, and present some first investigations using uni or multi-variate methods in association with re-sampling techniques. Specifically, because the number of variables is very high, we first reduce the data size and then use multivariate (CCA, PLS) techniques in association with re-sampling techniques.
机译:Imagen研究 - 一个非常大的欧洲研究项目 - 寻求识别和表征影响青少年心理健康的生物和环境因素。为此目的,联盟计划在8个神经影像学中心收集2000多个受试者的数据。这些数据包括神经影像数据,行为测试(最多5小时的测试),以及收集的白血样和加工,以获得每项受试者的650k单核苷酸多态性(SNP)。已经收集了超过1000个科目的数据。我们描述了这些数据的统计方面以及由这种大型成像遗传学研究(即,对于SNP的650k,每种神经镜50k数据)产生的多重比较问题的挑战。我们还建议了可能的策略,以及使用UNI或多变量方法与重新采样技术相关联的首次调查。具体而言,因为变量的数量非常高,我们首先减少数据大小,然后使用与重新采样技术相关联的多元(CCA,PLS)技术。

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