Diagnostic Genetic Unit, Careggi Hospital, Azienda Ospedaliera Universitaria Careggi, University of Florence, Florence, Italy.
Biostatistics. 2010 Jul;11(3):515-8. doi: 10.1093/biostatistics/kxq008. Epub 2010 Mar 5.
Array comparative genomic hybridization (aCGH) is a microarray technology that allows one to detect and map genomic alterations. The standard workflow of the aCGH data analysis consists of 2 steps: detecting the boundaries of the regions of changed copy number by means of a segmentation algorithm (break point identification) and then labeling each region as loss, neutral, or gain with a probabilistic framework (calling procedure). In this paper, we introduce a novel calling procedure based on a mixture of truncated normal distributions, named FastCall, that aims to give aberration probabilities to segmented aCGH data in a very fast and accurate way. Both on synthetic and real aCGH data, FastCall obtains excellent performances in terms of classification accuracy and running time.
阵列比较基因组杂交 (aCGH) 是一种微阵列技术，可用于检测和绘制基因组改变。aCGH 数据分析的标准工作流程包括 2 个步骤：通过分段算法（断点识别）检测改变拷贝数的区域的边界，然后使用概率框架（调用程序）将每个区域标记为缺失、中性或增益。在本文中，我们引入了一种基于截断正态混合分布的新的调用程序，命名为 FastCall，旨在非常快速和准确地为分段 aCGH 数据提供异常概率。在合成和真实的 aCGH 数据上，FastCall 在分类准确性和运行时间方面都取得了优异的性能。
