A User-Friendly Visualization Tool for Multi-Omics Data.
Sunghyun HuhMin-Sik KimPublished in: Proteomics (2020)
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.
Keyphrases
- electronic health record
- big data
- genome wide
- single cell
- papillary thyroid
- healthcare
- palliative care
- genome wide identification
- dna methylation
- mental health
- copy number
- squamous cell
- machine learning
- artificial intelligence
- mass spectrometry
- squamous cell carcinoma
- quality improvement
- lymph node metastasis
- genome wide analysis
- body composition
- label free
- liquid chromatography