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-KIDS:在超高维度右边审查设置中的新功能评估,适用于头部和部癌症

Atika Farzana Urmi¹, Chenlu Ke², Dipankar Bandyopadhyay¹

¹Department of Biostatistics, Virginia Commonwealth University, Richmond, Virginia, USA.

Statistics in medicine

|July 15, 2025

概括

我们开发了alpha-KIDS,这是一种用于识别头癌存活率数据中的关键遗传标记的新方法. 这种方法有助于预测患者的结果,并利用全基因组信息了解癌症进展.

科学领域:

基因组学就是基因组学.
生物信息学是一种生物信息学.
癌症研究癌症研究

背景情况:

来自测序技术的全基因组数据有助于头癌 (HNC) 的诊断和预后.
确定生存的预测标志物对于预后系统和了解癌症驱动因素至关重要.

研究的目的:

介绍alpha-KIDS,这是一个无模型的特征选程序,用于超高维度,右审查的生存数据.
确保对未知审查机制的稳定性,并控制错误发现率 (FDR).

主要方法:

一个两阶段的程序,涉及双重选与基于非参数的繁殖核的ANOVA统计数据.
一个统一的淘汰程序精炼特征集在FDR的控制下.

主要成果:

模拟研究证明了alpha-KIDS方法的有限样本特性和新性.
应用到癌症基因组图谱 (TCGA) 头癌生存数据中的应用.

结论:

阿尔法-KIDS方法有效地识别复杂的生存数据中的预测标记.
该R包aKIDS可用于实施这种强大的特征选程序.

关键词:

在FDR控制系统中,FDR控制器功能选功能选功能选功能选功能选头部和部癌症头部和部癌症的高维共变量.没有参数的非参数.权利审查 - 审查.

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