A statistical approach for array CGH data analysis

Background: Microarray-CGH experiments are used to detect and map chromosomal imbalances, by hybridizing targets of genomic DNA from a test and a reference sample to sequences immobilized on a slide. These probes are genomic DNA sequences (BACs) that are mapped on the genome. The signal has a spatial coherence that can be handled by specific statistical tools. Segmentation methods seem to be a natural framework for this purpose. A CGH profile can be viewed as a succession of segments that represent homogeneous regions in the genome whose BACs share the same relative copy number on average. We model a CGH profile by a random Gaussian process whose distribution parameters are affected by abrupt changes at unknown coordinates. Two major problems arise : to determine which parameters are affected by the abrupt changes (the mean and the variance, or the mean only), and the selection of the number of segments in the profile. Results: We demonstrate that existing methods for estimating the n...

• Type: Journal
• Year: 2005
• Where: BMCBI
• Authors: Franck Picard, Stéphane Robin, Marc Lavielle, Christian Vaisse, Jean-Jacques Daudin
• Keywords: Array Cgh Data, BMCBI 2005, CGH Profile, Genomic Dna