M Kreuz1, M Rosolowski, H Berger, C Schwaenen, S Wessendorf, M Loeffler, D Hasenclever. 1. University 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
Abstract
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 paper we 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 manually up 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.
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 paper we 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 manually up 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.
Authors: René Scholtysik; Markus Kreuz; Wolfram Klapper; Birgit Burkhardt; Alfred C Feller; Michael Hummel; Markus Loeffler; Maciej Rosolowski; Carsten Schwaenen; Rainer Spang; Harald Stein; Christoph Thorns; Lorenz Trümper; Inga Vater; Swen Wessendorf; Thorsten Zenz; Reiner Siebert; Ralf Küppers Journal: Haematologica Date: 2010-09-07 Impact factor: 9.941
Authors: Maciej Rosolowski; Jürgen Läuter; Dmitriy Abramov; Hans G Drexler; Michael Hummel; Wolfram Klapper; Roderick A F Macleod; Shoji Pellissery; Friedemann Horn; Reiner Siebert; Markus Loeffler Journal: PLoS One Date: 2013-11-04 Impact factor: 3.240