Detection of divergent genes in microbial aCGH experiments

Background: Array-based comparative genome hybridization (aCGH) is a tool for rapid comparison of genomes from different bacterial strains. The purpose of such analysis is to detect highly divergent or absent genes in a sample strain compared to an index strain. Development of methods for analyzing aCGH data has primarily focused on copy number abberations in cancer research. In microbial aCGH analyses, genes are typically ranked by log-ratios, and classification into divergent or present is done by choosing a cutoff log-ratio, either manually or by statistics calculated from the log-ratio distribution. As experimental settings vary considerably, it is not possible to develop a classical discriminant or statistical learning approach. Methods: We introduce a more efficient method for analyzing microbial aCGH data using a finite mixture model and a data rotation scheme. Using the average posterior probabilities from the model fitted to log-ratios before and after rotation, we get a scor...

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: Lars Snipen, Dirk Repsilber, Ludvig Nyquist, Ågot Aakra, Andreas Ziegler, Are Halvor Aastveit
• Keywords: ACGH, BMCBI 2006, Comparative Genome Hybridization, Divergent Genes