A modified Bayes information criterion with applications to the analysis of comparative genomic hybridization data
A modified Bayes information criterion with applications to the analysis of comparative genomic hybridization data
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DOI：
10.1111/j.1541-0420.2006.00662.x
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发表时间：
2007-03-01
期刊：
影响因子：
1.9
通讯作者：
Siegmund, David O.
中科院分区：
文献类型：
--
作者：
Zhang, Nancy R.;Siegmund, David O.
在分析变化点过程生成的数据时，一项关键挑战是确定变化点的数量。由于似然函数的不规则性，经典的贝叶斯信息准则 (BIC) 统计在这里效果不佳。通过贝叶斯因子的渐近逼近，我们推导了漂移变化的布朗运动模型的修正 BIC。修改后的 BIC 与经典 BIC 类似，第一项由对数似然组成，但不同之处在于惩罚模型维度的项。作为应用示例，这一新统计数据用于分析基于阵列的比较基因组杂交 (array-CGH) 数据。 Array-CGH 测量细胞样本每个基因组位置的染色体拷贝数，对于寻找肿瘤细胞中基因组缺失和扩增的区域非常有用。与现有方法相比，修改后的 BIC 在准确选择拷贝数变化的区域数量方面表现良好。与现有方法不同，它不依赖于调整参数或密集计算。因此它是公正的并且更容易理解和使用。
In the analysis of data generated by change-point processes, one critical challenge is to determine the number of change-points. The classic Bayes information criterion (BIC) statistic does not work well here because of irregularities in the likelihood function. By asymptotic approximation of the Bayes factor, we derive a modified BIC for the model of Brownian motion with changing drift. The modified BIC is similar to the classic BIC in the sense that the first term consists of the log likelihood, but it differs in the terms that penalize for model dimension. As an example of application, this new statistic is used to analyze array-based comparative genomic hybridization (array-CGH) data. Array-CGH measures the number of chromosome copies at each genome location of a cell sample, and is useful for finding the regions of genome deletion and amplification in tumor cells. The modified BIC performs well compared to existing methods in accurately choosing the number of regions of changed copy number. Unlike existing methods, it does not rely on tuning parameters or intensive computing. Thus it is impartial and easier to understand and to use.