Overlay Tool(C) for aCGHViewer(C) : An Analysis Module Built for aCGHViewer(C) used to Perform Comparisons of Data Derived from Different Microarray Platforms

被引:0
|
作者
Lo, Ken C. [1 ]
Shankar, Ganesh [1 ]
Turpaz, Yaron [2 ]
Bailey, Dione [2 ]
Rossi, Michael R. [1 ,3 ]
Burkhardt, Tania [1 ]
Liang, Ping [1 ]
Cowell, John K. [1 ]
机构
[1] Roswell Pk Canc Inst, Dept Canc Genet, Elm & Carlton Str,Buffalo, Buffalo, NY 14263 USA
[2] Affymetrix Inc, Santa Clara, CA 95051 USA
[3] Yale Univ, Sch Med, Dept Canc Genet, New Haven, CT 06520 USA
来源
CANCER INFORMATICS | 2007年 / 3卷
基金
美国国家卫生研究院;
关键词
Overlay Analysis; Microarray; ACGH; expression profi ling; CNAs; aCGHViewer;
D O I
暂无
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
The Overlay Tool(C) 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(C) 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(C) 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(C) (Shankar et al. 2006), which serves as a conduit to public databases such as UCSC and NCBI, to rapidly investigate genes of interest.
引用
收藏
页码:307 / 319
页数:13
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