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A User-Friendly Visualization Tool for Multi-Omics Data

Title
A User-Friendly Visualization Tool for Multi-Omics Data
Authors
Huh, SunghyunKim, Min-Sik
DGIST Authors
Huh, Sunghyun; Kim, Min-Sik
Issue Date
2020-11
Citation
Proteomics, 20(21-22), 2000136
Type
Article
Article Type
Article
Author Keywords
Clinical Proteomic Tumor Analysis Consortiumdata visualizationmulti-omics
ISSN
1615-9853
Abstract
The Clinical Proteomic Tumor Analysis Consortium (CPTAC) initiative has generated large multi-omic datasets for various cancers. Each dataset consists of common and differential data types, including genomics, epigenomics, transcriptomics, proteomics, and post-translational modifications data. They together make up a rich resource for researchers and clinicians interested in understanding cancer biology to draw from. Nevertheless, the complexity of these multi-omic datasets and a lack of an easily accessible analytical and visualization tool for exploring them continue to be a hurdle for those who are not trained in bioinformatics. In this issue, Calinawan et al. describe a user-friendly, web-based visualization platform named ProTrack for exploring the CPTAC clear cell renal cell carcinoma (ccRCC) dataset. Compared to other available visualization tools, ProTrack offers an easy yet powerful customization interface, solely dedicated to the CPTAC ccRCC dataset. Their tool enables ready inspection of potential associations between different data types within a single gene or across multiple genes without any need to code. Specific mutation types or phosphosites can also be easily looked up for any gene of interest. Calinawan et al. aim to extend their work into other CPTAC datasets, which will greatly contribute to the CPTAC as well as cancer biology community in general. © 2020 Wiley-VCH GmbH
URI
http://hdl.handle.net/20.500.11750/12586
DOI
10.1002/pmic.202000136
Publisher
John Wiley & Sons Ltd.
Related Researcher
  • Author Kim, Min-Sik Laboratory for QBIO and Precision Medicine
  • Research Interests Cancer Proteogenomics, Biomarker Discovery, Integrative Multi-Omics
Files:
There are no files associated with this item.
Collection:
Department of New BiologyLaboratory for QBIO and Precision Medicine1. Journal Articles


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