Next-Generation Clustered Heat Maps for fluent, interactive exploration of omic data: Cloud Pilot Supplement

 描述(申请人提供)：聚集热图(CHM)被称为后基因组生物学的无处不在的视觉图标，已经出现在成千上万的出版物中。我们在20世纪90年代初引入了中药，用于在DNA、RNA、蛋白质、代谢物和药物水平上可视化和分析分子图谱数据中的相似和不同模式。然而，这些中药是静态图像。我们想要的是一个基于CHM的交互式环境，用于深入探索基因组数据中的模式-CHM中，用户可以像在Google地图中那样进行缩放和导航，链接到各种外部信息源，动态重新着色，调用统计工具箱，保存所有必要的元数据 在几个月或几年后复制地图，并制作符合所有主要期刊标准的高分辨率图形。因此，我们开发了具有这些和许多其他功能的交互式“下一代”集群热图(NG-CHM)。NG-CHM已(I)收到了广泛的用户反馈；(Ii)被用于MD Anderson癌症中心的多个临床前和临床部门的研究；(Iii)在与癌症基因组图谱(TCGA)相关的三个公共门户网站上公开提供--总计&gt；1000个地图；(Iv)作为TCGA蛋白质组数据的主要分析和解释工具；以及(V)被几乎所有TCGA的疾病工作组使用。然而，它们还没有渗透到癌症研究界。我们现在建议成熟和加强NG-CHM的开发，引入额外的工具箱功能，增加用户友好性，增加“共享能力”，并优化环境，以适应非信息学专家的癌症生物学家和临床研究人员的需求和工作流程。最终产品将是一套交互式可视化资源，可以很容易地在研究小组成员之间共享，分发给同事，和/或作为链接到期刊页面上的静态印刷版的互动图形。目前提供了大量书面文件和教程视频；将在多个会议和机构举办动手讲习班。

 DESCRIPTION (provided by applicant): Clustered Heat Maps (CHMs) have been called the ubiquitous visual icons of post-genomic biology, having appeared in many thousands of publications. We introduced CHMs in the early 1990s for visualization and analysis of patterns of similarity and difference in molecular profile data at the DNA, RNA, protein, metabolite, and pharmacological levels. However, those CHMs were static images. What we wanted was an interactive CHM-based environment for deep exploration of patterns in omic data - CHMs in which one could zoom and navigate as in a Google map, link out to a variety of external information sources, re-color on the fly, invoke a statistical toolbox, save all metadata necessary to reproduce the map months or years later, and produce high- resolution graphics that meet the standards of all major journals. Accordingly, we have developed interactive "Next-Generation" Clustered Heat Maps (NG-CHMs) with those and many other capabilities. The NG-CHMs have (i) received extensive user feedback; (ii) been used for studies in multiple preclinical and clinical departments at MD Anderson Cancer Center; (iii) been provided publicly in three public web portals associated with The Cancer Genome Atlas (TCGA) -- with, in aggregate, >1,000 maps; (iv) served as the principal analytic and interpretive tools for proteomic data in TCGA; and (v) been employed in almost all of TCGA's Disease Working Groups. However, they have not yet permeated the cancer research community. We now propose to mature and harden the NG-CHM development, introducing additional toolbox features, increasing user-friendliness, increasing "share ability," and refining the environment to fit the needs and workflows of cancer biologists and clinical researchers who are not specialists in informatics. The end product will be a suite of interactive visualization resources that can easily be shared among members of a research team, distributed to colleagues, and/or serve as interactive graphics linked to the static print versions in journal pages. Extensive written documentation and tutorial videos are currently provided; hands-on workshops will be held at multiple meetings and institutions.