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

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.

[1]  Emmanuel Barillot,et al.  Analysis of array CGH data: from signal ratio to gain and loss of DNA regions , 2004, Bioinform..

[2]  S. Dudoit,et al.  Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. , 2002, Nucleic acids research.

[3]  R. Spang,et al.  A biologic definition of Burkitt's lymphoma from transcriptional and genomic profiling. , 2006, The New England journal of medicine.

[4]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[5]  Franck Picard,et al.  A statistical approach for array CGH data analysis , 2005, BMC Bioinformatics.

[6]  J Rahnenführer Image analysis for cDNA microarrays. , 2005, Methods of information in medicine.

[7]  R. Tibshirani,et al.  A method for calling gains and losses in array CGH data. , 2005, Biostatistics.

[8]  Jane Fridlyand,et al.  Bioinformatics Original Paper a Comparison Study: Applying Segmentation to Array Cgh Data for Downstream Analyses , 2022 .

[9]  D. Conrad,et al.  Global variation in copy number in the human genome , 2006, Nature.

[10]  Elena Marchiori,et al.  Breakpoint identification and smoothing of array comparative genomic hybridization data , 2004, Bioinform..

[11]  Wei Chen,et al.  CGHPRO – A comprehensive data analysis tool for array CGH , 2005, BMC Bioinformatics.

[12]  D Repsilber,et al.  Two-color Microarray Experiments , 2005, Methods of Information in Medicine.

[13]  Erhard Rahm,et al.  The GeWare data warehouse platform for the analysisof molecular-biological and clinical data , 2007, J. Integr. Bioinform..

[14]  Ajay N. Jain,et al.  Hidden Markov models approach to the analysis of array CGH data , 2004 .

[15]  Daniel Pinkel,et al.  Genomic microarrays in human genetic disease and cancer. , 2003, Human molecular genetics.

[16]  L. Feuk,et al.  Detection of large-scale variation in the human genome , 2004, Nature Genetics.

[17]  M. Wigler,et al.  Circular binary segmentation for the analysis of array-based DNA copy number data. , 2004, Biostatistics.

[18]  Sun-Yuan Kung,et al.  Accurate detection of aneuploidies in array CGH and gene expression microarray data , 2004, Bioinform..

[19]  Christian A. Rees,et al.  Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[20]  Ross Ihaka,et al.  Gentleman R: R: A language for data analysis and graphics , 1996 .

[21]  Qing-Rong Chen,et al.  Detection of low level genomic alterations by comparative genomic hybridization based on cDNA micro-arrays , 2005, Bioinform..

[22]  Peter J. Park,et al.  Comparative analysis of algorithms for identifying amplifications and deletions in array CGH data , 2005, Bioinform..