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.
Clustered Heat Maps (CHMs) have appeared in many thousands of publications for visualization of large-scale data on the molecular profiles of cancers. We have now produced prototype 'Next-Generation' Clustered Heat Maps (NG-CHMs), in which one can zoom and navigate (as in Google Maps) and link out to a variety of information sources on the web. We propose to mature NG-CHM technology for fluent use and sharing by biologists and clinical researchers who are not specialists in informatics, thus providing a major resource for continued progress in precision, individualized medicine for the benefit of patients and their families.
| Liu, Yang; Sethi, Nilay S; Hinoue, Toshinori et al. (2018) Comparative Molecular Analysis of Gastrointestinal Adenocarcinomas. Cancer Cell 33:721-735.e8 |
| Campbell, Joshua D; Yau, Christina; Bowlby, Reanne et al. (2018) Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas. Cell Rep 23:194-212.e6 |
| Berger, Ashton C; Korkut, Anil; Kanchi, Rupa S et al. (2018) A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers. Cancer Cell 33:690-705.e9 |
| Hoadley, Katherine A; Yau, Christina; Hinoue, Toshinori et al. (2018) Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer. Cell 173:291-304.e6 |
| Cancer Genome Atlas Research Network; Albert Einstein College of Medicine; Analytical Biological Services et al. (2017) Integrated genomic and molecular characterization of cervical cancer. Nature 543:378-384 |
| Farshidfar, Farshad; Zheng, Siyuan; Gingras, Marie-Claude et al. (2017) Integrative Genomic Analysis of Cholangiocarcinoma Identifies Distinct IDH-Mutant Molecular Profiles. Cell Rep 18:2780-2794 |
| Fishbein, Lauren; Leshchiner, Ignaty; Walter, Vonn et al. (2017) Comprehensive Molecular Characterization of Pheochromocytoma and Paraganglioma. Cancer Cell 31:181-193 |
| Cancer Genome Atlas Research Network; Analysis Working Group: Asan University; BC Cancer Agency et al. (2017) Integrated genomic characterization of oesophageal carcinoma. Nature 541:169-175 |
| Chen, F; Zhang, Y; Parra, E et al. (2017) Multiplatform-based molecular subtypes of non-small-cell lung cancer. Oncogene 36:1384-1393 |
| Cancer Genome Atlas Research Network. Electronic address: wheeler@bcm.edu; Cancer Genome Atlas Research Network (2017) Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma. Cell 169:1327-1341.e23 |
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