SeeGH – A software tool for visualization of whole genome array comparative genomic hybridization data

BACKGROUND: Array comparative genomic hybridization (CGH) is a technique which detects copy number differences in DNA segments. Complete sequencing of the human genome and the development of an array representing a tiling set of tens of thousands of DNA segments spanning the entire human genome has made high resolution copy number analysis throughout the genome possible. Since array CGH provides signal ratio for each DNA segment, visualization would require the reassembly of individual data points into chromosome profiles. RESULTS: We have developed a visualization tool for displaying whole genome array CGH data in the context of chromosomal location. SeeGH is an application that translates spot signal ratio data from array CGH experiments to displays of high resolution chromosome profiles. Data is imported from a simple tab delimited text file obtained from standard microarray image analysis software. SeeGH processes the signal ratio data and graphically displays it in a conventional CGH karyotype diagram with the added features of magnification and DNA segment annotation. In this process, SeeGH imports the data into a database, calculates the average ratio and standard deviation for each replicate spot, and links them to chromosome regions for graphical display. Once the data is displayed, users have the option of hiding or flagging DNA segments based on user defined criteria, and retrieve annotation information such as clone name, NCBI sequence accession number, ratio, base pair position on the chromosome, and standard deviation. CONCLUSIONS: SeeGH represents a novel software tool used to view and analyze array CGH data. The software gives users the ability to view the data in an overall genomic view as well as magnify specific chromosomal regions facilitating the precise localization of genetic alterations. SeeGH is easily installed and runs on Microsoft Windows 2000 or later environments

Computational Methods for the Analysis of Array Comparative Genomic Hybridization

Array comparative genomic hybridization (array CGH) is a technique for assaying the copy number status of cancer genomes. The widespread use of this technology has lead to a rapid accumulation of high throughput data, which in turn has prompted the development of computational strategies for the analysis of array CGH data. Here we explain the principles behind array image processing, data visualization and genomic profile analysis, review currently available software packages, and raise considerations for future software development

CGHPRO – A comprehensive data analysis tool for array CGH

BACKGROUND: Array CGH (Comparative Genomic Hybridisation) is a molecular cytogenetic technique for the genome wide detection of chromosomal imbalances. It is based on the co-hybridisation of differentially labelled test and reference DNA onto arrays of genomic BAC clones, cDNAs or oligonucleotides, and after correction for various intervening variables, loss or gain in the test DNA can be indicated from spots showing aberrant signal intensity ratios. Now that this technique is no longer confined to highly specialized laboratories and is entering the realm of clinical application, there is a need for a user-friendly software package that facilitates estimates of DNA dosage from raw signal intensities obtained by array CGH experiments, and which does not depend on a sophisticated computational environment. RESULTS: We have developed a user-friendly and versatile tool for the normalization, visualization, breakpoint detection and comparative analysis of array-CGH data. CGHPRO is a stand-alone JAVA application that guides the user through the whole process of data analysis. The import option for image analysis data covers several data formats, but users can also customize their own data formats. Several graphical representation tools assist in the selection of the appropriate normalization method. Intensity ratios of each clone can be plotted in a size-dependent manner along the chromosome ideograms. The interactive graphical interface offers the chance to explore the characteristics of each clone, such as the involvement of the clones sequence in segmental duplications. Circular Binary Segmentation and unsupervised Hidden Markov Model algorithms facilitate objective detection of chromosomal breakpoints. The storage of all essential data in a back-end database allows the simultaneously comparative analysis of different cases. The various display options facilitate also the definition of shortest regions of overlap and simplify the identification of odd clones. CONCLUSION: CGHPRO is a comprehensive and easy-to-use data analysis tool for array CGH. Since all of its features are available offline, CGHPRO may be especially suitable in situations where protection of sensitive patient data is an issue. It is distributed under GNU GPL licence and runs on Linux and Windows

Integrated functional visualization of eukaryotic genomes

BACKGROUND: Increasing amounts of data from large scale whole genome analysis efforts demands convenient tools for manipulation, visualization and investigation. Whole genome plots offer an intuitive window to the analysis. We describe two applications that enable users to easily plot and explore whole genome data from their own or other researchers' experiments. RESULTS: STRIPE and GFFtool (General Feature Format Tool) are softwares designed to support integration, visualization and exploration of whole genome data from eukaryotic genomes. STRIPE, in addition to providing a highly customizable and interactive data plot, provides access to numerous well-selected databases with updated information on all genes of a genome. GFFtool provides a user-friendly solution to integrating experimental data with the genomic information available in public databases. They also obviate the need for users to maintain large annotation resources, as they link to well-known resources using standard gene and protein identifiers. CONCLUSION: The programs provide the user with broad genomic overviews of data distribution, fast access to data of interest, and the ability to navigate speedily from one resource to another, and gain a better understanding of result of whole genome analysis experiments

Large fragment Bst DNA polymerase for whole genome amplification of DNA from formalin-fixed paraffin-embedded tissues

BACKGROUND: Formalin-fixed paraffin-embedded (FFPE) tissues represent the largest source of archival biological material available for genomic studies of human cancer. Therefore, it is desirable to develop methods that enable whole genome amplification (WGA) using DNA extracted from FFPE tissues. Multiple-strand Displacement Amplification (MDA) is an isothermal method for WGA that uses the large fragment of Bst DNA polymerase. To date, MDA has been feasible only for genomic DNA isolated from fresh or snap-frozen tissue, and yields a representational distortion of less than threefold. RESULTS: We amplified genomic DNA of five FFPE samples of normal human lung tissue with the large fragment of Bst DNA polymerase. Using quantitative PCR, the copy number of 7 genes was evaluated in both amplified and original DNA samples. Four neuroblastoma xenograft samples derived from cell lines with known N-myc gene copy number were also evaluated, as were 7 samples of non-small cell lung cancer (NSCLC) tumors with known Skp2 gene amplification. In addition, we compared the array comparative genomic hybridization (CGH)-based genome profiles of two NSCLC samples before and after Bst MDA. A median 990-fold amplification of DNA was achieved. The DNA amplification products had a very high molecular weight (> 23 Kb). When the gene content of the amplified samples was compared to that of the original samples, the representational distortion was limited to threefold. Array CGH genome profiles of amplified and non-amplified FFPE DNA were similar. CONCLUSION: Large fragment Bst DNA polymerase is suitable for WGA of DNA extracted from FFPE tissues, with an expected maximal representational distortion of threefold. Amplified DNA may be used for the detection of gene copy number changes by quantitative realtime PCR and genome profiling by array CGH

Genetic alteration and gene expression modulation during cancer progression

Cancer progresses through a series of histopathological stages. Progression is thought to be driven by the accumulation of genetic alterations and consequently gene expression pattern changes. The identification of genes and pathways involved will not only enhance our understanding of the biology of this process, it will also provide new targets for early diagnosis and facilitate treatment design. Genomic approaches have proven to be effective in detecting chromosomal alterations and identifying genes disrupted in cancer. Gene expression profiling has led to the subclassification of tumors. In this article, we will describe the current technologies used in cancer gene discovery, the model systems used to validate the significance of the genes and pathways, and some of the genes and pathways implicated in the progression of preneoplastic and early stage cancer

Integrative Genomic Analyses Identify BRF2 as a Novel Lineage-Specific Oncogene in Lung Squamous Cell Carcinoma

William Lockwood and colleagues show that the focal amplification of a gene, BRF2, on Chromosome 8p12 plays a key role in squamous cell carcinoma of the lung