A comparative analysis of computational approaches to relative protein quantification using peptide peak intensities in label-free LC-MS proteomics experiments.
A comparative analysis of computational approaches to relative protein quantification using peptide peak intensities in label-free LC-MS proteomics experiments.
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DOI：
10.1002/pmic.201200269
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发表时间：
2013-02
期刊：
影响因子：
3.4
通讯作者：
Webb-Robertson, Bobbie-Jo
中科院分区：
文献类型：
--
作者：
Matzke, Melissa M.;Brown, Joseph N.;Gritsenko, Marina A.;Metz, Thomas O.;Pounds, Joel G.;Rodland, Karin D.;Shukla, Anil K.;Smith, Richard D.;Waters, Katrina M.;McDermott, Jason E.;Webb-Robertson, Bobbie-Jo
液相色谱与质谱联用 (LC-MS) 广泛用于识别和定量复杂生物样品中的肽。特别是，无标记鸟枪蛋白质组学对于肽的鉴定以及随后获得样品的整体蛋白质谱非常有效。因此，这种方法被广泛用于发现研究。通常，这些发现研究的目的是识别受某些感兴趣条件（例如疾病、暴露）影响的蛋白质。然而，对于复杂的生物样品，无标记 LC-MS 蛋白质组学实验测量肽，并不能直接产生蛋白质数量。因此，蛋白质定量必须根据一种或多种测量的肽来推断。近年来，已经发表了许多计算无标记 LC-MS 数据的相对蛋白质定量的计算方法。在这篇综述中，我们研究了最常用的定量方法，以根据峰值强度值计算相对蛋白质丰度，评估其各自的优点，并讨论使用各种计算方法时面临的挑战。
Liquid chromatography coupled with mass spectrometry (LC-MS) is widely used to identify and quantify peptides in complex biological samples. In particular, label-free shotgun proteomics is highly effective for the identification of peptides and subsequently obtaining a global protein profile of a sample. As a result, this approach is widely used for discovery studies. Typically, the objective of these discovery studies is to identify proteins that are affected by some condition of interest (e.g., disease, exposure). However, for complex biological samples, label-free LC-MS proteomics experiments measure peptides and do not directly yield protein quantities. Thus, protein quantification must be inferred from one or more measured peptides. In recent years many computational approaches to compute relative protein quantification of label-free LC-MS data have been published. In this review, we examine the most commonly employed quantification approaches to compute relative protein abundance from peak intensity values, evaluate their individual merits, and discuss challenges in the use of the various computational approaches.
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