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An evaluation of Monte-Carlo logic and logicFS motivated by a study of the regulation of gene expression in heart failure

机译：对心力衰竭中基因表达调控的研究对蒙特卡洛逻辑和逻辑FS的评估

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摘要

Monte-Carlo (MC) Logic and Logic Feature Selection (logicFS) identify binary predictors of outcome using repeated iterations of logic regression, a variable selection method that identifies Boolean combinations of predictors. Both methods compute the frequency with which predictors appear in the model with the output of the logicFS program providing specific summaries of predictor form. We sought to identify variables related to transcription factor-related regulation of gene expression differences in a study of failing and non-failing hearts. Results based broadly on the frequency of occurrence of predictors into the MC Logic or logicFS models were similar. However key to logicFS are variable importance measures (VIMs), which augment the frequency metrics and seek to evaluate a predictor's contribution to classification. Analytic work and simulation studies indicate that the VIM vary as a function of the joint prevalence of outcome and predictor. Thus, findings from logicFS have limited generalizability, particularly with respect to case-control studies where the prevalence of outcome is determined by study design. Interpretation of VIM for those variables with near-zero or negative values is particularly ambiguous. Additional issues with interpretability arise because the VIM are strongly affected by other variables selected into the model but logicFS does not explicitly identify these variables in its output.
机译：蒙特卡洛（MC）逻辑和逻辑特征选择（logicFS）使用逻辑回归的重复迭代来确定结果的二进制预测变量，这是一种识别预测变量的布尔组合的变量选择方法。两种方法都可以计算预测变量出现在模型中的频率，其中logicFS程序的输出将提供预测变量形式的特定摘要。我们试图在心脏衰竭和非衰竭的研究中确定与转录因子相关的基因表达差异调控相关的变量。大致基于MC Logic或逻辑FS模型中预测变量出现频率的结果相似。然而，LogicFS的关键是可变重要性度量（VIM），它可以提高频率指标并试图评估预测变量对分类的贡献。分析工作和模拟研究表明，VIM随结果和预测因素的联合患病率而变化。因此，LogicalFS的发现具有局限性，尤其是在病例对照研究中，结果的普遍性由研究设计决定。对于具有接近零或负值的变量，VIM的解释特别含糊。由于VIM受到模型中选择的其他变量的强烈影响，因此会出现其他可解释性问题，但是logicFS不会在其输出中明确标识这些变量。

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  • 来源
    《Journal of applied statistics》 |2014年第10期|1956-1975|共20页
  • 作者

    Yun Lu; Sridhar Hannenhalli; Tom Cappola; Mary Putt;

  • 作者单位

    Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA;

    Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD, USA;

    Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA;

    Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA;

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  • 正文语种 eng
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  • 关键词

    heart failure; logic regression; Monte-Carlo (MC) logic; logicFS; bootstrap; classification;

    机译：心脏衰竭;逻辑回归蒙特卡洛（MC）逻辑;逻辑FS;引导程序分类;

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