Ji Hongkai, Wong Wing Hung
Department of Statistics, Harvard University, Cambridge, MA 02138, USA.
Bioinformatics. 2005 Sep 15;21(18):3629-36. doi: 10.1093/bioinformatics/bti593. Epub 2005 Jul 26.
Tiling array is a new type of microarray that can be used to survey genomic transcriptional activities and transcription factor binding sites at high resolution. The goal of this paper is to develop effective statistical tools to identify genomic loci that show transcriptional or protein binding patterns of interest.
A two-step approach is proposed and is implemented in TileMap. In the first step, a test-statistic is computed for each probe based on a hierarchical empirical Bayes model. In the second step, the test-statistics of probes within a genomic region are used to infer whether the region is of interest or not. Hierarchical empirical Bayes model shrinks variance estimates and increases sensitivity of the analysis. It allows complex multiple sample comparisons that are essential for the study of temporal and spatial patterns of hybridization across different experimental conditions. Neighboring probes are combined through a moving average method (MA) or a hidden Markov model (HMM). Unbalanced mixture subtraction is proposed to provide approximate estimates of false discovery rate for MA and model parameters for HMM.
TileMap is freely available at http://biogibbs.stanford.edu/~jihk/TileMap/index.htm.
http://biogibbs.stanford.edu/~jihk/TileMap/index.htm (includes coloured versions of all figures).
平铺阵列是一种新型微阵列，可用于高分辨率地检测基因组转录活性和转录因子结合位点。本文的目标是开发有效的统计工具，以识别显示出感兴趣的转录或蛋白质结合模式的基因组位点。
提出了一种两步法并在TileMap中实现。第一步，基于分层经验贝叶斯模型为每个探针计算一个检验统计量。第二步，使用基因组区域内探针的检验统计量来推断该区域是否令人感兴趣。分层经验贝叶斯模型缩小了方差估计并提高了分析的灵敏度。它允许进行复杂的多样本比较，这对于研究不同实验条件下杂交的时空模式至关重要。相邻探针通过移动平均法（MA）或隐马尔可夫模型（HMM）进行组合。提出了不平衡混合减法，以提供MA的错误发现率的近似估计和HMM的模型参数。
TileMap可从http://biogibbs.stanford.edu/~jihk/TileMap/index.htm免费获取。
http://biogibbs.stanford.edu/~jihk/TileMap/index.htm（包括所有图的彩色版本）。
