ProbMetab: an R package for Bayesian probabilistic annotation of LC-MS-based metabolomics
ProbMetab: an R package for Bayesian probabilistic annotation of LC-MS-based metabolomics
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DOI：
10.1093/bioinformatics/btu019
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发表时间：
2014-05-01
期刊：
影响因子：
5.8
通讯作者：
Vencio, Ricardo Z. N.
中科院分区：
文献类型：
--
作者：
Silva, Ricardo R.;Jourdan, Fabien;Vencio, Ricardo Z. N.
我们提出了ProbMetab，一个R包，促进自动概率液相色谱-质谱为基础的代谢组注释的实质性改进。推理引擎核心基于贝叶斯模型，该模型实现为（i）允许将不同来源的实验数据和元数据系统地纳入模型中，并采用替代方法计算似然函数，以及（ii）允许敏感地选择具有生物学意义的生化反应数据库作为Dirichletcategorical先验分布。此外，为了确保系统生物学家对结果进行解释，我们在网络中显示注释，如果候选代谢物是已知生化反应的底物/产物，则将观察到的质量峰连接起来。该图可以与其他基于图的分析（例如部分相关网络）叠加，以可视化方案导出到Cytoscape，具有Web和独立版本。
We present ProbMetab, an R package that promotes substantial improvement in automatic probabilistic liquid chromatography-mass spectrometry-based metabolome annotation. The inference engine core is based on a Bayesian model implemented to (i) allow diverse source of experimental data and metadata to be systematically incorporated into the model with alternative ways to calculate the likelihood function and (ii) allow sensitive selection of biologically meaningful biochemical reaction databases as Dirichletcategorical prior distribution. Additionally, to ensure result interpretation by system biologists, we display the annotation in a network where observed mass peaks are connected if their candidate metabolites are substrate/ product of known biochemical reactions. This graph can be overlaid with other graph-based analysis, such as partial correlation networks, in a visualization scheme exported to Cytoscape, with web and stand-alone versions.