NormaCurve: a SuperCurve-based method that simultaneously quantifies and normalizes reverse phase protein array data.
NormaCurve: a SuperCurve-based method that simultaneously quantifies and normalizes reverse phase protein array data.
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DOI：
10.1371/journal.pone.0038686
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发表时间：
2012
期刊：
影响因子：
3.7
通讯作者：
de Koning L
中科院分区：
文献类型：
--
作者：
Troncale S;Barbet A;Coulibaly L;Henry E;He B;Barillot E;Dubois T;Hupé P;de Koning L
反相蛋白质阵列（RPPA）是一种功能强大的斑点印迹技术，可以同时研究大量样品中的蛋白质表达水平以及翻译后修饰。然而，RPPA数据的正确解释仍然是其广泛应用及其转化为临床研究的主要挑战。令人满意的定量工具可用于从连续稀释曲线评估相对蛋白质表达水平。然而，目前缺乏适当的工具，使外部变异来源的数据标准化。在这里，我们提出了一种名为NormaCurve的新方法，可以同时量化和标准化RPPA数据。为此，我们修改了定量方法SuperCurve，以便包括（i）背景荧光，（ii）点样蛋白总量的变化和（iii）阵列上的空间偏差的归一化。使用一个spike-in设计与纯化的蛋白质，我们测试了不同的模型，以正确估计归一化的相对表达水平的能力。最佳性能模型NormaCurve考虑了不含一抗的阴性对照阵列、用总蛋白染色剂染色的阵列和空间协变量。我们表明，这种归一化是可重现的，我们讨论了获得稳健数据所需的连续稀释次数和重复次数。因此，我们提供了一个现成的RPPA数据，这应该有利于解释和发展这一有前途的技术可靠和可重复的标准化方法。原始数据、脚本和NormaCurve包可在以下网站获得：http://microarrays.curie.fr。
Reverse phase protein array (RPPA) is a powerful dot-blot technology that allows studying protein expression levels as well as post-translational modifications in a large number of samples simultaneously. Yet, correct interpretation of RPPA data has remained a major challenge for its broad-scale application and its translation into clinical research. Satisfying quantification tools are available to assess a relative protein expression level from a serial dilution curve. However, appropriate tools allowing the normalization of the data for external sources of variation are currently missing. Here we propose a new method, called NormaCurve, that allows simultaneous quantification and normalization of RPPA data. For this, we modified the quantification method SuperCurve in order to include normalization for (i) background fluorescence, (ii) variation in the total amount of spotted protein and (iii) spatial bias on the arrays. Using a spike-in design with a purified protein, we test the capacity of different models to properly estimate normalized relative expression levels. The best performing model, NormaCurve, takes into account a negative control array without primary antibody, an array stained with a total protein stain and spatial covariates. We show that this normalization is reproducible and we discuss the number of serial dilutions and the number of replicates that are required to obtain robust data. We thus provide a ready-to-use method for reliable and reproducible normalization of RPPA data, which should facilitate the interpretation and the development of this promising technology. The raw data, the scripts and the NormaCurve package are available at the following web site: http://microarrays.curie.fr.
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DOI：
10.1093/bioinformatics/btn663
发表时间：
2009-03-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Zhang L;Wei Q;Mao L;Liu W;Mills GB;Coombes K
通讯作者：
Coombes K
影响因子：
5.8
作者：
Mircean, C;Shmulevich, I;Zhang, W
通讯作者：
Zhang, W
影响因子：
5.4
作者：
Tabus, Ioan;Hategan, Andrea;Astola, Jaakko
通讯作者：
Astola, Jaakko
影响因子：
5.7
作者：
Tibes, Raoul;Qiu, YiHua;Kornblau, Steven M.
通讯作者：
Kornblau, Steven M.
DOI：
10.1158/1078-0432.ccr-09-2502
发表时间：
2010-05-15
期刊：
Clinical cancer research : an official journal of the American Association for Cancer Research
影响因子：
--
作者：
Carey MS;Agarwal R;Gilks B;Swenerton K;Kalloger S;Santos J;Ju Z;Lu Y;Zhang F;Coombes KR;Miller D;Huntsman D;Mills GB;Hennessy BT
通讯作者：
Hennessy BT