Including shared peptides for estimating protein abundances: A significant improvement for quantitative proteomics
Including shared peptides for estimating protein abundances: A significant improvement for quantitative proteomics
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DOI：
10.1002/pmic.201100660
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发表时间：
2012-09-01
期刊：
影响因子：
3.4
通讯作者：
Zivy, Michel
中科院分区：
文献类型：
--
作者：
Blein-Nicolas, Melisande;Xu, Hao;Zivy, Michel
从肽强度推断蛋白质丰度是定量蛋白质组学的关键步骤。当给定蛋白质考虑许多肽时，推断必然更准确。然而，不同蛋白质共享的肽所带来的信息通常被丢弃。我们提出了一个基于分层建模的统计框架来包含该信息。我们的方法基于对所有定量肽的同步分析，处理生物和技术错误以及肽效应。此外，我们提出了一种适合分析大数据集的实用实现。与基于一次分析一种蛋白质（不包括共享肽）的方法相比，我们的方法被证明对于估计蛋白质丰度和测试丰度变化要可靠得多。源代码可在 http://pappso.inra.fr/bioinfo/all_p/ 获取。
Inferring protein abundances from peptide intensities is the key step in quantitative proteomics. The inference is necessarily more accurate when many peptides are taken into account for a given protein. Yet, the information brought by the peptides shared by different proteins is commonly discarded. We propose a statistical framework based on a hierarchical modeling to include that information. Our methodology, based on a simultaneous analysis of all the quantified peptides, handles the biological and technical errors as well as the peptide effect. In addition, we propose a practical implementation suitable for analyzing large data sets. Compared to a method based on the analysis of one protein at a time (that does not include shared peptides), our methodology proved to be far more reliable for estimating protein abundances and testing abundance changes. The source codes are available at http://pappso.inra.fr/bioinfo/all_p/.