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A Bayes testing approach to metagenomic profiling in bacteria

机译:用于细菌宏基因组分析的贝叶斯测试方法

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Using next generation sequencing (NGS) data, we use a multinomial with a Dirichlet prior to detect the presence of bacteria in a metagenomic sample via marginal Bayes testing for each bacterial strain. The NGS reads per strain are counted fractionally with each read contributing an equal amount to each strain it might represent. The threshold for detection is strain-dependent and we apply a correction for the dependence amongst the (NGS) reads by finding the knee in a curve representing a tradeoff between detecting too many strains and not enough strains. As a check, we evaluate the joint posterior probabilities for the presence of two strains of bacteria and find relatively little dependence. We apply our techniques to two data sets and compare our results with the results found by the Human Microbiome Project. We conclude with a discussion of the issues surrounding multiple corrections in a Bayes context.
机译:使用下一代测序(NGS)数据,我们使用Dirichlet多项式,然后通过对每个细菌菌株进行边际Bayes测试来检测宏基因组学样品中细菌的存在。对每个菌株的NGS读数进行分数计数,每次读数对其可能代表的每个菌株的贡献相等。检测阈值取决于应变,我们通过在表示检测到过多应变与不足应变之间进行权衡的曲线中找到拐点来对(NGS)读数之间的相关性进行校正。作为检查,我们评估了两种细菌菌株的联合后验概率,并发现相对较少的依赖性。我们将我们的技术应用于两个数据集,并将结果与​​人类微生物组计划的结果进行比较。我们以贝叶斯上下文中围绕多次更正的问题进行讨论。

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