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蛋白质裂解物阵列的非参数定量

Non-parametric quantification of protein lysate arrays.

作者信息

Hu Jianhua, He Xuming, Baggerly Keith A, Coombes Kevin R, Hennessy Bryan T J, Mills Gordon B

机构信息

Department of Bioinformatics and Computational Biology, University of Texas M.D. Anderson Cancer Center, TX, USA.

出版信息

Bioinformatics. 2007 Aug 1;23(15):1986-94. doi: 10.1093/bioinformatics/btm283. Epub 2007 Jun 28.

Abstract

MOTIVATION

Proteins play a crucial role in biological activity, so much can be learned from measuring protein expression and post-translational modification quantitatively. The reverse-phase protein lysate arrays allow us to quantify the relative expression levels of a protein in many different cellular samples simultaneously. Existing approaches to quantify protein arrays use parametric response curves fit to dilution series data. The results can be biased when the parametric function does not fit the data.

RESULTS

We propose a non-parametric approach which adapts to any monotone response curve. The non-parametric approach is shown to be promising via both simulation and real data studies; it reduces the bias due to model misspecification and protects against outliers in the data. The non-parametric approach enables more reliable quantification of protein lysate arrays.

AVAILABILITY

Code to implement the proposed method in the statistical package R is available at: http://odin.mdacc.tmc.edu/jhu/lysatearray-analysis/

摘要

动机

蛋白质在生物活性中起着至关重要的作用,因此通过定量测量蛋白质表达和翻译后修饰可以了解很多信息。反相蛋白质裂解物阵列使我们能够同时定量许多不同细胞样品中蛋白质的相对表达水平。现有的定量蛋白质阵列的方法使用适合稀释系列数据的参数响应曲线。当参数函数不适合数据时,结果可能会有偏差。

结果

我们提出了一种适用于任何单调响应曲线的非参数方法。通过模拟和实际数据研究表明,该非参数方法很有前景;它减少了由于模型错误指定而导致的偏差,并能抵御数据中的异常值。该非参数方法能够更可靠地定量蛋白质裂解物阵列。

可用性

在统计软件包R中实现所提出方法的代码可在以下网址获取:http://odin.mdacc.tmc.edu/jhu/lysatearray-analysis/

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