Department of New Biology, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, 42988, Republic of Korea.
Proteomics. 2020 Nov;20(21-22):e2000136. doi: 10.1002/pmic.202000136. Epub 2020 Sep 3.
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.
临床蛋白质组肿瘤分析联盟（CPTAC）计划已经为各种癌症生成了大型的多组学数据集。每个数据集都包含常见和差异的数据类型，包括基因组学、表观基因组学、转录组学、蛋白质组学和翻译后修饰数据。它们共同构成了一个丰富的资源，供对理解癌症生物学感兴趣的研究人员和临床医生参考。然而，这些多组学数据集的复杂性以及缺乏易于访问的分析和可视化工具来探索它们，对于没有接受过生物信息学培训的人来说仍然是一个障碍。在本期中，Calinawan 等人描述了一个名为 ProTrack 的用户友好的基于网络的可视化平台，用于探索 CPTAC 透明细胞肾细胞癌（ccRCC）数据集。与其他可用的可视化工具相比，ProTrack 提供了一个简单而强大的定制界面，专门针对 CPTAC ccRCC 数据集。他们的工具允许在单个基因或多个基因内轻松检查不同数据类型之间的潜在关联，而无需编写代码。还可以轻松查找任何感兴趣基因的特定突变类型或磷酸化位点。Calinawan 等人旨在将他们的工作扩展到其他 CPTAC 数据集，这将极大地促进 CPTAC 以及癌症生物学领域的发展。
