A New Smoothing Model for Analyzing Array CGH Data

Array based comparative genomic hybridization (CGH) is a molecular cytogenetic method for the detection of chromosomal imbalances and it has been extensively used for studying copy number alterations in various cancer types. Our method captures both the intrinsic spatial change of genome hybridization intensities, and the physical distance between adjacent probes along a chromosome which are not uniform. In this paper, we introduce a dual-tree complex wavelet transform method with the bivariate shrinkage estimator into array CGH data smoothing study. We tested the proposed method on both simulated data and real data, and the results demonstrated superior performance of our method in comparison with extant methods.