Development and Implementation of an Analysis Tool for Array-based Comparative Genomic Hybridization

M. Kreuz; M. Rosolowski; H. Berger; C. Schwaenen; S. Wessendorf; M. Loeffler; D. Hasenclever

doi:10.1160/ME9064

Methods of Information in Medicine, Inhaltsverzeichnis

Methods Inf Med 2007; 46(05): 608-613
DOI: 10.1160/ME9064

Paper

Schattauer GmbH

Development and Implementation of an Analysis Tool for Array-based Comparative Genomic Hybridization

M. Kreuz

¹Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Leipzig, Germany

,

M. Rosolowski

¹Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Leipzig, Germany

,

H. Berger

¹Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Leipzig, Germany

,

C. Schwaenen

²Department of Internal Medicine III, University Hospital of Ulm, Ulm, Germany

,

S. Wessendorf

²Department of Internal Medicine III, University Hospital of Ulm, Ulm, Germany

,

M. Loeffler

¹Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Leipzig, Germany

,

D. Hasenclever

¹Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Leipzig, Germany

› Institutsangaben

Abstract

Summary

Objectives: Array-comparative genomic hybridization (aCGH) is a high-throughput method to detect and map copy number aberrations in the genome. Multi-step analysis of high-dimensional data requires an integrated suite of bioinformatic tools. In this paperwe detail an analysis pipeline for array CGH data.

Methods: We developed an analysis tool for array CGH data which supports single and multi-chip analyses as well as combined analyses with paired mRNA gene expression data. The functions supporting relevant steps of analysis were implemented using the open source software R and combined as package aCGHPipeline. Analysis methods were illustrated using 189 CGH arrays of aggressive B-cell lymphomas.

Results: The package covers data input, quality control, normalization, segmentation and classification. For multi-chip analysis aCGHPipeline offers an algorithm for automatic delineation of recurrent regions. This task was performed manuallyup to now. The package also supports combined analysis with mRNA gene expression data. Outputs consist of HTML documents to facilitate communication with clinical partners.

Conclusions: The R package aCGHPipeline supports basic tasks of single and multi-chip analysis of array CGH data.

Keywords

Array CGH - DNA copy number - gene expression - gene dosage

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Referenzen

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