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首页> 外文期刊>BMC Bioinformatics >JCDSA: a joint covariate detection tool for survival analysis on tumor expression profiles
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JCDSA: a joint covariate detection tool for survival analysis on tumor expression profiles

机译：JCDSA：联合协变量检测工具，用于对肿瘤表达谱进行生存分析

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Survival analysis on tumor expression profiles has always been a key issue for subsequent biological experimental validation. It is crucial how to select features which closely correspond to survival time. Furthermore, it is important how to select features which best discriminate between low-risk and high-risk group of patients. Common features derived from the two aspects may provide variable candidates for prognosis of cancer. Based on the provided two-step feature selection strategy, we develop a joint covariate detection tool for survival analysis on tumor expression profiles. Significant features, which are not only consistent with survival time but also associated with the categories of patients with different survival risks, are chosen. Using the miRNA expression data (Level 3) of 548 patients with glioblastoma multiforme (GBM) as an example, miRNA candidates for prognosis of cancer are selected. The reliability of selected miRNAs using this tool is demonstrated by 100 simulations. Furthermore, It is discovered that significant covariates are not directly composed of individually significant variables. Joint covariate detection provides a viewpoint for selecting variables which are not individually but jointly significant. Besides, it helps to select features which are not only consistent with survival time but also associated with prognosis risk. The software is available at http://bio-nefu.com/resource/jcdsa .
机译：肿瘤表达谱的生存分析一直是后续生物学实验验证的关键问题。选择与生存时间密切相关的特征至关重要。此外，重要的是如何选择能够最好地区分低危和高危患者组的特征。从这两个方面得出的共同特征可能为癌症的预后提供可变的候选者。基于提供的两步特征选择策略，我们开发了联合协变量检测工具来对肿瘤表达谱进行生存分析。选择不仅与生存时间一致而且与具有不同生存风险的患者类别相关的重要特征。以548名多形性胶质母细胞瘤（GBM）患者的miRNA表达数据（第3级）为例，选择了可用于癌症预后的miRNA候选对象。通过100次仿真证明了使用此工具选择的miRNA的可靠性。此外，发现重要协变量不是直接由单个重要变量组成。联合协变量检测为选择不是单独而是共同重要的变量提供了一个观点。此外，它有助于选择不仅与生存时间一致而且与预后风险相关的特征。该软件可从http://bio-nefu.com/resource/jcdsa获得。

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