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Motivation: Array Comparative Genomic Hybridization (aCGH) is used to scanthe entire genome for variations in DNA copy number. A central task in theanalysis of aCGH data is the segmentation into groups of probes sharing thesame DNA copy number. Some well known segmentation methods suffer from verylong running times, preventing interactive data analysis. Results: We suggest anew segmentation method based on wavelet decomposition and thresholding, whichdetects significant breakpoints in the data. Our algorithm is over 1,000 timesfaster than leading approaches, with similar performance. Another key advantageof the proposed method is its simplicity and flexibility. Due to its intuitivestructure it can be easily generalized to incorporate several types of sideinformation. Here we consider two extensions which include side informationindicating the reliability of each measurement, and compensating for a changingvariability in the measurement noise. The resulting algorithm outperformsexisting methods, both in terms of speed and performance, when applied on realhigh density CGH data. Availability: Implementation is available under softwaretab at: http://www.ee.technion.ac.il/Sites/People/YoninaEldar/ Contact:yonina@ee.technion.ac.il

A Fast and Flexible Method for the Segmentation of aCGH Data