Comprehensive study of DNA copy number analysis using Sigma filter

DNA copy number aberrations are characteristic of many genomic diseases including cancer. Microarray-based Comparative Genomic Hybridization (aCGH) is a recently developed high-throughput technique used to detect DNA copy number (DCN) aberrations. Unfortunately, the observed copy number changes are corrupted by noise, making aberration boundaries hard to detect. In the first part of this paper, we propose a novel technique to analyze DCN aberrations based on the Sigma filter algorithm. We establish its superior performance for denoising DCN data and low computational complexity as compared to previous techniques. We present a comparison study between our approach and other smoothing and statistical approaches, the wavelet-based, LookA-head, CGH segmentation and HMM. We provide examples using real data to illustrate the performance of the algorithms. In the second part of this paper, we extend our algorithm by considering the effect of nonuniform physical distance between the probes in the aCGH data. Finally, we provide simulated and real data examples to study this effect.