论文信息 - δ-Clustering of Monotone Profiles

δ-Clustering of Monotone Profiles

In Chaps. and 8, we discussed several testing procedures to detect differentially expressed genes with monotone relationship with respect to dose. The second question of primary interest in dose-response studies is the nature (or the shape of curve) of the dose-response relationship. In the context of dose-response microarray experiments, we wish to group (or classify) genes with similar dose-response relationship. Similar to the previous chapters, the subset of genes with monotone relationship is of interest.

[1] Ziv Shkedy,et al. Testing for Trends in Dose-Response Microarray Experiments: A Comparison of Several Testing Procedures, Multiplicity and Resampling-Based Inference , 2007, Statistical applications in genetics and molecular biology.

[2] J. A. Hartigan,et al. A k-means clustering algorithm , 1979 .

[3] Dhammika Amaratunga,et al. Microarray learning with ABC. , 2008, Biostatistics.

[4] Y. Benjamini,et al. Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[5] T. Caliński,et al. A dendrite method for cluster analysis , 1974 .

[6] Lothar Thiele,et al. A systematic comparison and evaluation of biclustering methods for gene expression data , 2006, Bioinform..

[7] George M. Church,et al. Biclustering of Expression Data , 2000, ISMB.

[8] Leo Breiman,et al. Random Forests , 2001, Machine Learning.

[9] Robert Tibshirani,et al. Estimating the number of clusters in a data set via the gap statistic , 2000 .

[10] Arlindo L. Oliveira,et al. Biclustering algorithms for biological data analysis: a survey , 2004, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[11] Richard A. Johnson,et al. Applied Multivariate Statistical Analysis , 1983 .

[12] S. Dudoit,et al. Resampling-based multiple testing for microarray data analysis , 2003 .

[13] Teuvo Kohonen,et al. Self-Organizing Maps , 2010 .