STAC :: Array CGH (aCGH) Analysis

Recurrent genomic DNA amplifications and deletions characterize cancer genomes and often contribute to disease evolution. These regions often harbor critical cancer genes, such as amplification of the MYCN oncogene at 2p24 in neuroblastoma. Moreover, recent evidence suggests that fixed genomic abnormalities such as CNAs may be more predictive of treatment response than mRNA or protein expression levels.

Genomic CNAs can now be detected at high resolution using microarray-based techniques.  By most accounts, Array CGH (aCGH) has become the most important technique for accurately quantifying copy number changes (gains and losses) in genomic DNA. 

However, robust statistical methods are needed to identify non-random gains and losses across multiple experiments/samples. While at the University of Pennsylvania, my colleagues and I developed a new method called Significance Testing for Aberrant Copy number (STAC) to address this need. STAC utilizes two complementary statistics in combination with a novel search strategy.

For the first time, I am offering licensing opportunities for the STAC algorithm and software.  This software implementation that I developed is modular and can fit into any commercial or proprietary Laboratory Information Management System (LIMS).  In addition, I am offering a comprehensive system for detecting cancer-related genomic aberrations that is based on STAC. 

Please download the Cancer Gene Discovery System brochure (MS Word) or a PowerPoint presentation for the STAC-based system here. If you have access to o2 mobile broadband or anything similar, you can download them even if you are on the go.

Also the original publication of STAC in J Genome Research article is available online.