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Development and implementation of an analysis tool for array-based comparative genomic hybridization.

M Kreuz1, M Rosolowski, H Berger

  • 1University of Leipzig, Institute for Medical Informatics, Statistics and Epidemiology, (IMISE), Haertelstr. 16-18, 04107 Leipzig, and Department of Internal Medicine III, University Hospital of Ulm, Germany. markus.kreuz@imise.uni-leipzig.de

Methods of Information in Medicine
|October 17, 2007
PubMed
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This study introduces aCGHPipeline, an R package for analyzing array comparative genomic hybridization (aCGH) data. It streamlines single and multi-chip analyses, aiding in the detection of genomic copy number aberrations.

Area of Science:

  • Genomics
  • Bioinformatics
  • Cancer Research

Background:

  • Array-comparative genomic hybridization (aCGH) is crucial for detecting genomic copy number aberrations.
  • Analyzing high-dimensional aCGH data necessitates integrated bioinformatic tools.

Purpose of the Study:

  • To detail an analysis pipeline for array CGH data.
  • To present the aCGHPipeline R package for efficient data analysis.

Main Methods:

  • Developed the aCGHPipeline R package using open-source software.
  • Implemented functions for data input, quality control, normalization, segmentation, and classification.
  • Illustrated methods using 189 CGH arrays from aggressive B-cell lymphomas.

Main Results:

Related Experiment Videos

  • The package supports single and multi-chip analyses, including combined analysis with mRNA gene expression data.
  • Introduced an algorithm for automatic delineation of recurrent regions in multi-chip analysis.
  • Outputs are generated as HTML documents for enhanced communication.

Conclusions:

  • The aCGHPipeline R package effectively supports essential single and multi-chip array CGH data analysis tasks.
  • Automates previously manual processes, improving efficiency in genomic analysis.