Random frog: An efficient reversible jump Markov Chain Monte Carlo-like approach for variable selection with applications to gene selection and disease classification
Random frog: An efficient reversible jump Markov Chain Monte Carlo-like approach for variable selection with applications to gene selection and disease classification
复制标题
随机青蛙：一种有效的可逆跳跃马尔可夫链蒙特卡罗方法，用于变量选择及其在基因选择和疾病分类中的应用
DOI：
10.1016/j.aca.2012.06.031
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发表时间：
2012-08-31
影响因子：
6.2
通讯作者：
Liang, Yi-Zeng
中科院分区：
文献类型：
--
作者：
Li, Hong-Dong;Xu, Qing-Song;Liang, Yi-Zeng
疾病相关基因的识别在基于微阵列的疾病诊断中是一项挑战，在这种疾病诊断中，样本量往往是有限的。在已有的方法中，可逆跳跃马尔可夫链蒙特卡罗(RJMCMC)方法被证明是非常有前途的变量选择方法。然而，RJMCMC算法的设计和应用需要例如针对先前分布的特殊标准。此外，从模型的联合后验分布进行模拟的计算量很大，甚至在数学上可能很难处理。这些缺点可能会限制RJMCMC算法的应用。因此，需要开发既具有RJMCMC方法的优点，又高效且易于遵循的疾病相关基因选择算法。在这里，我们报告了一种类似RJMCMC的方法，称为随机青蛙，它具有RJMCMC方法的优点，并且更容易实现。使用结肠和雌激素基因表达数据集，我们表明随机青蛙在识别区分基因方面是有效的。排在前两位的基因分别是Z50753、U00968和Y10871_at、Z22536_at。(GNU通用公共许可证2.0版的源代码可在以下网址免费向非商业用户提供：http://code.google.com/p/randomfrog/.)(C)爱思唯尔出版的2012年。
The identification of disease-relevant genes represents a challenge in microarray-based disease diagnosis where the sample size is often limited. Among established methods, reversible jump Markov Chain Monte Carlo (RJMCMC) methods have proven to be quite promising for variable selection. However, the design and application of an RJMCMC algorithm requires, for example, special criteria for prior distributions. Also, the simulation from joint posterior distributions of models is computationally extensive, and may even be mathematically intractable. These disadvantages may limit the applications of RJMCMC algorithms. Therefore, the development of algorithms that possess the advantages of RJMCMC methods and are also efficient and easy to follow for selecting disease-associated genes is required. Here we report a RJMCMC-like method, called random frog that possesses the advantages of RJMCMC methods and is much easier to implement. Using the colon and the estrogen gene expression datasets, we show that random frog is effective in identifying discriminating genes. The top 2 ranked genes for colon and estrogen are Z50753, U00968, and Y10871_at, Z22536_at, respectively. (The source codes with GNU General Public License Version 2.0 are freely available to non-commercial users at: http://code.google.com/p/randomfrog/.) (C) 2012 Published by Elsevier B.V.