Using free and open-source bioconductor packages to analyze array comparative genomics hybridization (aCGH) data

Whole-genome array Comparative Genomics Hybridization (aCGH) can be used to scan chromosomes for deletions and amplifications. Because of the increased accessibility of many commercial platforms, a lot of cancer researchers have used aCGH to study tumorigenesis or to predict clinical outcomes. Each data set is typically in several hundred thousands to one million rows of hybridization measurements. Thus, statistical analysis is a key to unlock the knowledge obtained from an aCGH study. We review several free and open-source packages in Bioconductor and provide example codes to run the analysis. The analysis of aCGH data provides insights of genomic abnormalities of cancers.