CBioProfiler: A Web and Standalone Pipeline for Cancer Biomarker and Subtype Characterization.

Xiaoping Liu, Zisong Wang, Hongjie Shi, Sheng Li, Xinghuan Wang
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Abstract

Cancer is a leading cause of death worldwide, and the identification of biomarkers and subtypes that can predict the long-term survival of cancer patients is essential for their risk stratification, treatment, and prognosis. However, there are currently no standardized tools for exploring cancer biomarkers or subtypes. In this study, we introduced Cancer Biomarker and subtype Profiler (CBioProfiler), a web server and standalone application that includes two pipelines for analyzing cancer biomarkers and subtypes. The cancer biomarker pipeline consists of five modules for identifying and annotating cancer survival-related biomarkers using multiple survival-related machine learning algorithms. The cancer subtype pipeline includes three modules for data preprocessing, subtype identification using multiple unsupervised machine learning methods, and subtype evaluation and validation. CBioProfiler also includes CuratedCancerPrognosisData, a novel R package that integrates reviewed and curated gene expression and clinical data from 268 studies. These studies cover 43 common blood and solid tumors and draw upon 47,686 clinical samples. The web server is available at https://www.cbioprofiler.com/ and https://cbioprofiler.znhospital.cn/CBioProfiler/, and the standalone app and source code can be found at https://github.com/liuxiaoping2020/CBioProfiler.

CBioProfiler:用于癌症生物标记物和亚型特征描述的网络和独立管道。
癌症是导致全球死亡的主要原因之一,而确定能够预测癌症患者长期生存的生物标志物和亚型对于癌症患者的风险分层、治疗和预后至关重要。然而,目前还没有用于探索癌症生物标志物或亚型的标准化工具。在这项研究中,我们介绍了癌症生物标记物和亚型分析器(CBioProfiler),它是一个网络服务器和独立应用程序,包括两个用于分析癌症生物标记物和亚型的管道。癌症生物标志物管道由五个模块组成,用于使用多种与生存相关的机器学习算法识别和注释与癌症生存相关的生物标志物。癌症亚型管道包括三个模块,分别用于数据预处理、使用多种无监督机器学习方法进行亚型识别以及亚型评估和验证。CBioProfiler 还包括 CuratedCancerPrognosisData,这是一个新颖的 R 软件包,整合了来自 268 项研究的经过审查和整理的基因表达和临床数据。这些研究涵盖 43 种常见的血液肿瘤和实体瘤,提取了 47,686 份临床样本。网络服务器位于 https://www.cbioprofiler.com/ 和 https://cbioprofiler.znhospital.cn/CBioProfiler/,独立应用程序和源代码位于 https://github.com/liuxiaoping2020/CBioProfiler。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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