VAMP: Visualization and analysis of array-CGH, transcriptome and other molecular profiles

MOTIVATION Microarray-based CGH (Comparative Genomic Hybridization), transcriptome arrays and other large-scale genomic technologies are now routinely used to generate a vast amount of genomic profiles. Exploratory analysis of this data is crucial in helping to understand the data and to help form biological hypotheses. This step requires visualization of the data in a meaningful way to visualize the results and to perform first level analyses. RESULTS We have developed a graphical user interface for visualization and first level analysis of molecular profiles. It is currently in use at the Institut Curie for cancer research projects involving CGH arrays, transcriptome arrays, SNP (single nucleotide polymorphism) arrays, loss of heterozygosity results (LOH), and Chromatin ImmunoPrecipitation arrays (ChIP chips). The interface offers the possibility of studying these different types of information in a consistent way. Several views are proposed, such as the classical CGH karyotype view or genome-wide multi-tumor comparison. Many functionalities for analyzing CGH data are provided by the interface, including looking for recurrent regions of alterations, confrontation to transcriptome data or clinical information, and clustering. Our tool consists of PHP scripts and of an applet written in Java. It can be run on public datasets at http://bioinfo.curie.fr/vamp AVAILABILITY The VAMP software (Visualization and Analysis of array-CGH,transcriptome and other Molecular Profiles) is available upon request. It can be tested on public datasets at http://bioinfo.curie.fr/vamp. The documentation is available at http://bioinfo.curie.fr/vamp/doc.

[1]  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.

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

[3]  Calum MacAulay,et al.  SeeGH – A software tool for visualization of whole genome array comparative genomic hybridization data , 2004, BMC Bioinformatics.

[4]  N. Carter,et al.  Array Comparative Genomic Hybridization Analysis of Colorectal Cancer Cell Lines and Primary Carcinomas , 2004, Cancer Research.

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

[6]  H. Döhner,et al.  Matrix‐based comparative genomic hybridization: Biochips to screen for genomic imbalances , 1997, Genes, chromosomes & cancer.

[7]  Jane Fridlyand,et al.  High-resolution analysis of DNA copy number alterations in colorectal cancer by array-based comparative genomic hybridization. , 2004, Carcinogenesis.

[8]  Y. Nakamura,et al.  Allelotype of colorectal carcinomas. , 1989, Science.

[9]  M. Shapero,et al.  High-resolution analysis of DNA copy number using oligonucleotide microarrays. , 2004, Genome research.

[10]  W. Kuo,et al.  High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays , 1998, Nature Genetics.

[11]  Elena Marchiori,et al.  Chromosomal Breakpoint Detection in Human Cancer , 2003, EvoWorkshops.

[12]  Ali S. Hadi,et al.  Finding Groups in Data: An Introduction to Chster Analysis , 1991 .

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

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

[15]  D. Albertson,et al.  Chromosome aberrations in solid tumors , 2003, Nature Genetics.

[16]  Emmanuel Barillot,et al.  Spatial normalization of array-CGH data , 2006, BMC Bioinformatics.

[17]  Céline Rouveirol,et al.  Bioinformatics Original Paper Computation of Recurrent Minimal Genomic Alterations from Array-cgh Data , 2022 .

[18]  Peter J. Rousseeuw,et al.  Finding Groups in Data: An Introduction to Cluster Analysis , 1990 .

[19]  L. Recht,et al.  High-resolution genome-wide mapping of genetic alterations in human glial brain tumors. , 2005, Cancer research.

[20]  Tom H. Pringle,et al.  The human genome browser at UCSC. , 2002, Genome research.

[21]  Emmanuel Barillot,et al.  Preferential Occurrence of Chromosome Breakpoints within Early Replicating Regions in Neuroblastoma , 2005, Cell cycle.

[22]  John Quackenbush,et al.  CGHAnalyzer: a stand-alone software package for cancer genome analysis using array-based DNA copy number data , 2005, Bioinform..

[23]  J. Lieb,et al.  ChIP-chip: considerations for the design, analysis, and application of genome-wide chromatin immunoprecipitation experiments. , 2004, Genomics.

[24]  Rui Li,et al.  Array-based comparative genomic hybridization reveals recurrent chromosomal aberrations and Jab1 as a potential target for 8q gain in hepatocellular carcinoma. , 2005, Carcinogenesis.

[25]  Keith W. Jones,et al.  Whole genome DNA copy number changes identified by high density oligonucleotide arrays , 2004, Human Genomics.

[26]  Paul H. C. Eilers,et al.  Quantile smoothing of array CGH data , 2005, Bioinform..

[27]  J. Fridlyand,et al.  Rare amplicons implicate frequent deregulation of cell fate specification pathways in oral squamous cell carcinoma , 2005, Oncogene.

[28]  Ajay N. Jain,et al.  Assembly of microarrays for genome-wide measurement of DNA copy number , 2001, Nature Genetics.

[29]  M. McMahon,et al.  Analysis of genomic DNA alterations and mRNA expression patterns in a panel of human pancreatic cancer cell lines , 2005, Genes, chromosomes & cancer.

[30]  Eugene Berezikov,et al.  CONREAL web server: identification and visualization of conserved transcription factor binding sites , 2005, Nucleic Acids Res..

[31]  Randy D Gascoyne,et al.  Comprehensive whole genome array CGH profiling of mantle cell lymphoma model genomes. , 2004, Human molecular genetics.

[32]  Jaime Prilusky,et al.  SPACE: a suite of tools for protein structure prediction and analysis based on complementarity and environment , 2005, Nucleic Acids Res..

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

[34]  J. Schimenti,et al.  Synapsis or silence , 2005, Nature Genetics.

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

[36]  D. Pinkel,et al.  Array comparative genomic hybridization and its applications in cancer , 2005, Nature Genetics.

[37]  Bradley P. Coe,et al.  A tiling resolution DNA microarray with complete coverage of the human genome , 2004, Nature Genetics.

[38]  Wen-Lin Kuo,et al.  Array-based comparative genomic hybridization for genome-wide screening of DNA copy number in bladder tumors. , 2003, Cancer research.