%0 Journal Article %1 Kreuz.2007 %A Kreuz, M. %A Rosolowski, M. %A Berger, H. %A Schwaenen, C. %A Wessendorf, S. %A Loeffler, Markus %A Hasenclever, Dirk %D 2007 %J Methods of information in medicine %K IMISE-Publikationen %N 5 %P 608–613 %T Development and implementation of an analysis tool for array-based comparative genomic hybridization %V 46 %X 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.

@article{Kreuz.2007, 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.}, added-at = {2014-10-15T15:04:07.000+0200}, author = {Kreuz, M. and Rosolowski, M. and Berger, H. and Schwaenen, C. and Wessendorf, S. and Loeffler, Markus and Hasenclever, Dirk}, biburl = {https://www.bibsonomy.org/bibtex/290d7be94d5b002f6c170a3be9eec731b/drtester}, interhash = {c319085ab2960542e5651f155209bc43}, intrahash = {90d7be94d5b002f6c170a3be9eec731b}, journal = {Methods of information in medicine}, keywords = {IMISE-Publikationen}, number = 5, pages = {608–613}, timestamp = {2014-12-03T00:08:44.000+0100}, title = {Development and implementation of an analysis tool for array-based comparative genomic hybridization}, volume = 46, year = 2007 }