计算机科学
工作流程
软件
数据库
大数据
数据科学
作者
D. R. Mani,Myranda Maynard,Ramani B. Kothadia,Karsten Krug,Karen E. Christianson,David I. Heiman,Karl R. Clauser,Chet Birger,Gad Getz,Steven A. Carr
出处
期刊:Nature Methods
[Springer Nature]
日期:2021-06-01
卷期号:18 (6): 580-582
被引量:5
标识
DOI:10.1038/s41592-021-01176-6
摘要
ABSTRACT Proteogenomics involves the integrative analysis of genomic, transcriptomic, proteomic and post-translational modification data produced by next-generation sequencing and mass spectrometry-based proteomics. Several publications by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and others have highlighted the impact of proteogenomics in enabling deeper insight into the biology of cancer and identification of potential drug targets. In order to encapsulate the complex data processing required for proteogenomics, and provide a simple interface to deploy a range of algorithms developed for data analysis, we have developed PANOPLY—a cloud-based platform for automated and reproducible proteogenomic data analysis. A wide array of algorithms have been implemented, and we highlight the application of PANOPLY to the analysis of cancer proteogenomic data.
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