Chari Raj, Lockwood William W, Coe Bradley P, Chu Anna, Macey Devon, Thomson Andrew, Davies Jonathan J, MacAulay Calum, Lam Wan L
Department of Cancer Genetics and Developmental Biology, British Columbia Cancer Research Centre, Vancouver, BC, Canada.
BMC Genomics. 2006 Dec 27;7:324. doi: 10.1186/1471-2164-7-324.
The prevalence of high resolution profiling of genomes has created a need for the integrative analysis of information generated from multiple methodologies and platforms. Although the majority of data in the public domain are gene expression profiles, and expression analysis software are available, the increase of array CGH studies has enabled integration of high throughput genomic and gene expression datasets. However, tools for direct mining and analysis of array CGH data are limited. Hence, there is a great need for analytical and display software tailored to cross platform integrative analysis of cancer genomes.
We have created a user-friendly java application to facilitate sophisticated visualization and analysis such as cross-tumor and cross-platform comparisons. To demonstrate the utility of this software, we assembled array CGH data representing Affymetrix SNP chip, Stanford cDNA arrays and whole genome tiling path array platforms for cross comparison. This cancer genome database contains 267 profiles from commonly used cancer cell lines representing 14 different tissue types.
In this study we have developed an application for the visualization and analysis of data from high resolution array CGH platforms that can be adapted for analysis of multiple types of high throughput genomic datasets. Furthermore, we invite researchers using array CGH technology to deposit both their raw and processed data, as this will be a continually expanding database of cancer genomes. This publicly available resource, the System for Integrative Genomic Microarray Analysis (SIGMA) of cancer genomes, can be accessed at http://sigma.bccrc.ca.
基因组高分辨率分析的普及使得对多种方法和平台所产生信息进行综合分析成为必要。尽管公共领域中的大多数数据是基因表达谱，并且有可用的表达分析软件，但阵列比较基因组杂交（array CGH）研究的增加使得高通量基因组和基因表达数据集的整合成为可能。然而，用于直接挖掘和分析阵列CGH数据的工具有限。因此，迫切需要专门针对癌症基因组跨平台综合分析的分析和显示软件。
我们创建了一个用户友好的Java应用程序，以促进复杂的可视化和分析，如跨肿瘤和跨平台比较。为了证明该软件的实用性，我们收集了代表Affymetrix SNP芯片、斯坦福cDNA阵列和全基因组平铺路径阵列平台的阵列CGH数据进行交叉比较。这个癌症基因组数据库包含来自代表14种不同组织类型的常用癌细胞系的267个图谱。
在本研究中，我们开发了一个用于可视化和分析来自高分辨率阵列CGH平台数据的应用程序，该程序可适用于分析多种类型的高通量基因组数据集。此外，我们邀请使用阵列CGH技术的研究人员存入他们的原始数据和处理后的数据，因为这将是一个不断扩展的癌症基因组数据库。这个公开可用的资源，即癌症基因组综合基因组微阵列分析系统（SIGMA），可通过http://sigma.bccrc.ca访问。
