Overlay Tool© for aCGHViewer©: An analysis module built for aCGHViewer© used to perform comparisons of data derived from different microarray platforms

• Type of Material: Article
• Authors: Ken C. Lo, Roswell Park Cancer Institute; Ganesh Shankar, Roswell Park Cancer Institute; Yaron Turpaz, Affymetrix, Inc.; Dione Bailey, Affymetrix, Inc.; Michael Rossi, Emory University; Tania Burkhardt, Roswell Park Cancer Institute; Ping Liang, Roswell Park Cancer Institute; John K. Cowell, Roswell Park Cancer Institute
• Language: English
• Date: 2007-12-01
• Publisher: Libertas Academica
• Publication Version: Final Published Version
• Copyright Statement: © 2007 The authors
• License: Creative Commons Attribution 3.0 Unported
• Final Published Version (URL): http://www.la-press.com/overlay-tool-for-acghviewer-an-analysis-module-built-for-acghviewer-us-article-a324
• Title of Journal or Parent Work: Cancer Informatics
• ISSN: 1176-9351
• Volume: 3
• Start Page: 307
• End Page: 319
• Grant/Funding Information: This work was supported in part by the Thrasher Research Fund, and CA 104504 (JKC) and CA 16056 Cancer Center Support Grant for Roswell Park Cancer Institute from the National Institutes of Health.
• Keywords: Overlay Analysis; Microarray; CNAs; ACGH; expression profiling; aCGHViewer
• Research Categories: Health Sciences, Radiology; Health Sciences, Oncology

Abstract

The Overlay Tool© has been developed to combine high throughput data derived from various microarray platforms. This tool analyzes high-resolution correlations between gene expression changes and either copy number abnormalities (CNAs) or loss of heterozygosity events detected using array comparative genomic hybridization (aCGH). Using an overlay analysis which is designed to be performed using data from multiple microarray platforms on a single biological sample, the Overlay Tool© identifies potentially important genes whose expression profiles are changed as a result of losses, gains and amplifications in the cancer genome. In addition, the Overlay Tool© will incorporate loss of heterozygosity (LOH) probability data into this overlay procedure. To facilitate this analysis, we developed an application which computationally combines two or more high throughput datasets (e.g. aCGH/expression) into a single categorized dataset for visualization and interrogation using a gene-centric approach. As such, data from virtually any microarray platform can be incorporated without the need to remap entire datasets individually. The resultant categorized (overlay) data set can be conveniently viewed using our in-house visualization tool, aCGHViewer© (Shankar et al. 2006), which serves as a conduit to public databases such as UCSC and NCBI, to rapidly investigate genes of interest.