| Title: | A new look towards BAC-based array CGH through a comprehensive comparison with oligo-based array CGH |
| Authors: | Wicker, Nicolas Carles, Annaick Mills, Ian G Wolf, Maija Veerakumarasivam, Abhi Edgren, Henrik Boileau, Fabrice Wasylyk, Bohdan Schalken, Jack A Neal, David E Kallioniemi, Olli Poch, Olivier |
| Issue Date: | 29-Mar-2007 |
| Citation: | BMC Genomics 2007, 8:84 |
| Abstract: | Abstract Background Currently, two main technologies are used for screening of DNA copy number; the BAC (Bacterial Artificial Chromosome) and the recently developed oligonucleotide-based CGH (Chromosomal Comparative Genomic Hybridization) arrays which are capable of detecting small genomic regions with amplification or deletion. The correlation as well as the discriminative power of these platforms has never been compared statistically on a significant set of human patient samples. Results In this paper, we present an exhaustive comparison between the two CGH platforms, undertaken at two independent sites using the same batch of DNA from 19 advanced prostate cancers. The comparison was performed directly on the raw data and a significant correlation was found between the two platforms. The correlation was greatly improved when the data were averaged over large chromosomic regions using a segmentation algorithm. In addition, this analysis has enabled the development of a statistical model to discriminate BAC outliers that might indicate microevents. These microevents were validated by the oligo platform results. Conclusion This article presents a genome-wide statistical validation of the oligo array platform on a large set of patient samples and demonstrates statistically its superiority over the BAC platform for the Identification of chromosomic events. Taking advantage of a large set of human samples treated by the two technologies, a statistical model has been developed to show that the BAC platform could also detect microevents. |
| Description: | RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are. |
| URI: | http://www.dspace.cam.ac.uk/handle/1810/238038 http://dx.doi.org/10.1186/1471-2164-8-84 |
| Appears in Collections: | Scholarly works - Oncology |
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