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
1   Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Leipzig, Germany
,
M. Rosolowski
1   Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Leipzig, Germany
,
H. Berger
1   Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Leipzig, Germany
,
C. Schwaenen
2   Department of Internal Medicine III, University Hospital of Ulm, Ulm, Germany
,
S. Wessendorf
2   Department of Internal Medicine III, University Hospital of Ulm, Ulm, Germany
,
M. Loeffler
1   Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Leipzig, Germany
,
D. Hasenclever
1   Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Leipzig, Germany
› Author Affiliations
Further Information

Publication History

Publication Date:
22 January 2018 (online)

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.

 
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