Feb 12, 2005

A statistical approach for array CGH data analysis

BMC Bioinformatics
Franck PicardJean-Jacques Daudin

Abstract

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. We demonstrate that existing methods for estimating the number of segments are not well adapted in the case of array CGH data, and we propose an adaptive criterion that detects previously mapped chromosomal aberrations. The performances of this method are discussed based on simulations and publicly available data sets. Then w...Continue Reading

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Citations

Mentioned in this Paper

In Silico
Biologic Segmentation
RNA Conformation
Gene Dosage
Genome
Computer Graphics
Genetic Markers
Bacterial Artificial Chromosomes
Genome Mapping
Computer Programs and Programming

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