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WebaCGH: an interactive online tool for the analysis and display of array comparative genomic hybridisation data
Casey Frankenberger1, Xiaolin Wu, Jerry Harmon
1Laboratory of Molecular Technology, Scientific Application International Corporation (SAIC) - Frederick, Inc., National Cancer Institute - Frederick, Frederick, Maryland, USA.
Applied Bioinformatics
|May 26, 2006
Summary
This study introduces WebaCGH, a web tool for analyzing gene copy number variations and transcription profiles. It helps identify chromosomal abnormalities in diseases like cancer.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- Gene copy number variations are implicated in various pathologies, including cancer.
- Array comparative genomic hybridization (aCGH) offers high-resolution detection of chromosomal gains and losses.
- Comparing aCGH with gene transcription profiles reveals the impact of DNA copy number on gene expression.
Purpose of the Study:
- To develop an integrated online software tool, WebaCGH, for analyzing aCGH and gene transcription data.
- To facilitate the identification and visualization of significant aberrant chromosomal regions.
- To provide a platform for long-term storage and retrieval of experimental data.
Main Methods:
- WebaCGH integrates aCGH and gene transcription results from multiple experiments.
- It employs a local Z-score threshold and moving averages for identifying significant aberrant regions.
- Results are displayed graphically with interactive features, including zoom and external database linking.
Main Results:
- WebaCGH enables direct comparison of DNA copy number variations with gene transcription profiles.
- The tool provides high-resolution visualization of chromosomal gains and losses.
- Users can store and retrieve data indefinitely for further analysis.
Conclusions:
- WebaCGH is a valuable, freely accessible web application for researchers studying gene copy number variations and their impact on transcription.
- The tool aids in the identification of chromosomal abnormalities relevant to cancer and developmental diseases.
- Its user-friendly interface and data management capabilities enhance genomic analysis workflows.
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