A hierarchical Bayesian model for flexible module discovery in three-way time-series data.
A hierarchical Bayesian model for flexible module discovery in three-way time-series data.
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DOI：
10.1093/bioinformatics/btv228
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发表时间：
2015-06-15
期刊：
影响因子：
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通讯作者：
Shamir R
中科院分区：
文献类型：
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作者：
Amar D;Yekutieli D;Maron-Katz A;Hendler T;Shamir R
动机：检测协调活动的模块是大型生物学研究分析的基础。对于二维数据（例如基因×患者），这通常通过聚类或双聚类来完成。最近，随着时间的推移监测患者的研究增加了另一个维度。在这种情况下，分析更具挑战性，特别是当时间测量不同步时。因此需要能够分析三向数据的新方法。结果：我们提出了一种在三向数据中寻找连贯且灵活的模块的新算法。我们的方法可以识别出现在多个患者中的核心模块以及这些包含额外基因的核心模块的患者特异性增强。我们的算法基于分层贝叶斯数据模型和吉布斯采样。该算法在模拟和真实数据上都优于现有方法。该方法成功地从基因表达的时间序列测量中剖析了感染性休克反应的关键组成部分。检测到的患者特异性模块增强可为疾病结果提供信息。在分析受试者休息时的脑功能磁共振成像时间序列时，它检测到了所涉及的相关大脑区域。可用性和实现：R 代码和数据可在 http://acgt.cs.tau.ac.il/twigs/ 上获取。联系方式：rshamir@tau.ac.il 补充信息：补充数据可在生物信息学在线获取。
Motivation: Detecting modules of co-ordinated activity is fundamental in the analysis of large biological studies. For two-dimensional data (e.g. genes × patients), this is often done via clustering or biclustering. More recently, studies monitoring patients over time have added another dimension. Analysis is much more challenging in this case, especially when time measurements are not synchronized. New methods that can analyze three-way data are thus needed. Results: We present a new algorithm for finding coherent and flexible modules in three-way data. Our method can identify both core modules that appear in multiple patients and patient-specific augmentations of these core modules that contain additional genes. Our algorithm is based on a hierarchical Bayesian data model and Gibbs sampling. The algorithm outperforms extant methods on simulated and on real data. The method successfully dissected key components of septic shock response from time series measurements of gene expression. Detected patient-specific module augmentations were informative for disease outcome. In analyzing brain functional magnetic resonance imaging time series of subjects at rest, it detected the pertinent brain regions involved. Availability and implementation: R code and data are available at http://acgt.cs.tau.ac.il/twigs/. Contact: rshamir@tau.ac.il Supplementary information: Supplementary data are available at Bioinformatics online.