Variable Selection in the Chlamydia Pneumoniae Lung Infection Study

Yuan Kang, N. Billor
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引用次数: 1

Abstract

In this study, the data based on nucleic acid amplication tech- niques (Polymerase chain reaction) consisting of 23 dierent transcript vari- ables which are involved to investigate genetic mechanism regulating chlamy- dial infection disease by measuring two dierent outcomes of muring C. pneumonia lung infection (disease expressed as lung weight increase and C. pneumonia load in the lung), have been analyzed. A model with fewer reduced transcript variables of interests at early infection stage has been obtained by using some of the traditional (stepwise regression, partial least squares regression (PLS)) and modern variable selection methods (least ab- solute shrinkage and selection operator (LASSO), forward stagewise regres- sion and least angle regression (LARS)). Through these variable selection methods, the variables of interest are selected to investigate the genetic mechanisms that determine the outcomes of chlamydial lung infection. The transcript variables Tim3, GATA3, Lacf, Arg2 (X4, X5, X8 and X13) are being detected as the main variables of interest to study the C. pneumonia disease (lung weight increase) or C. pneumonia lung load outcomes. Models including these key variables may provide possible answers to the problem of molecular mechanisms of chlamydial pathogenesis.
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肺炎衣原体肺部感染研究中的变量选择
在本研究中,基于核酸扩增技术(聚合酶链式反应)的数据由23个不同的转录物组成,这些转录物通过测量肺炎支原体肺部感染的两个不同结果(以肺部重量增加和肺部肺炎支原体载量表示的疾病)来研究调节重婚感染疾病的遗传机制,已经进行了分析。通过使用一些传统的(逐步回归、偏最小二乘回归(PLS))和现代变量选择方法(最小二乘收缩和选择算子(LASSO)、前向阶段回归和最小角度回归(LARS)),获得了一个在感染早期具有较少感兴趣的减少转录变量的模型。通过这些变量选择方法,选择感兴趣的变量来研究决定衣原体肺部感染结果的遗传机制。转录物变量Tim3、GATA3、Lacf、Arg2(X4、X5、X8和X13)被检测为研究肺炎梭菌疾病(肺重量增加)或肺炎梭菌肺负荷结果的主要感兴趣变量。包括这些关键变量的模型可能为衣原体发病机制的分子机制问题提供可能的答案。
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