MVisAGe Identifies Concordant and Discordant Genomic Alterations of Driver Genes in Squamous Tumors.
MVisAGe Identifies Concordant and Discordant Genomic Alterations of Driver Genes in Squamous Tumors.
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DOI：
10.1158/0008-5472.can-17-3464
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发表时间：
2018-06-15
期刊：
影响因子：
11.2
通讯作者：
Hayes DN
中科院分区：
文献类型：
--
作者：
Walter V;Du Y;Danilova L;Hayward MC;Hayes DN
多个基因组数据库的综合分析现在在癌症分析研究中很常见。这些数据为许多计算实验提供了机会，但分析管道有限。cBioPortal和Regulome Explorer等工具虽然有用，但不容易通过编程访问或在本地实现。在这里，我们介绍MVisAGe R软件包，它允许用户量化两个基因组数据库之间的基因水平关联，以研究基因组改变的影响（例如DNA拷贝数变化对基因表达的影响）。根据潜在基因的基因组位置可视化Pearson/斯皮尔曼相关系数为进行探索性分析提供了一种强大而新颖的工具。我们通过分析三个公开的癌症数据集来证明其实用性。我们的方法突出了chr 11 q13中的典型癌基因，这些癌基因在表达和拷贝数之间表现出最强的相关性，包括CCND 1和CTTN，这些基因在主要报告中未通过拷贝数分析鉴定。我们证明了chr 3q上共享癌基因的高度一致性使用，但chr 11 q上的癌基因使用作为HPV感染状态的函数显著不同。chr 19区域显示甲基化和基因表达之间的显着关联被确定，如以前未报告的miRNA基因表达协会，可能有助于上皮间质转化。
Integrated analyses of multiple genomic datatypes are now common in cancer profiling studies. Such data present opportunities for numerous computational experiments, yet analytic pipelines are limited. Tools such as the cBioPortal and Regulome Explorer, while useful, are not easy to access programmatically or implement locally. Here we introduce the MVisAGe R package, which allows users to quantify gene-level associations between two genomic datatypes in order to investigate the effect of genomic alterations (e.g. DNA copy number changes on gene expression). Visualizing Pearson/Spearman correlation coefficients according to the genomic positions of the underlying genes provides a powerful yet novel tool for conducting exploratory analyses. We demonstrate its utility by analyzing three publicly available cancer datasets. Our approach highlights canonical oncogenes in chr11q13 that displayed the strongest associations between expression and copy number, including CCND1 and CTTN, genes not identified by copy number analysis in the primary reports. We demonstrate highly concordant usage of shared oncogenes on chr3q, yet strikingly diverse oncogene usage on chr11q as a function of HPV infection status. Regions of chr19 that display remarkable associations between methylation and gene expression were identified, as were previously unreported miRNA-gene expression associations that may contribute to the epithelial-to-mesenchymal transition.