Global gel-free proteomic analysis by mass spectrometry has been widely used as an important tool for exploring complex biological systems at the whole genome level. Simultaneous analysis of a large number of protein species is a complicated and challenging task. The challenges exist throughout all stages of a global gel-free proteomic analysis: experimental design, peptide/protein identification, data preprocessing and normalization, and inferential analysis. In addition to various efforts to improve the analytical technologies, statistical methodologies have been applied in all stages of proteomic analyses to help extract relevant information efficiently from large proteomic datasets. In this review, we summarize current applications of statistics in several stages of global gel-free proteomic analysis by mass spectrometry. We discuss the challenges associated with the applications of various statistical tools. Whenever possible, we also propose potential solutions on how to improve the data collection and interpretation for mass-spectrometry-based global proteomic analysis using more sophisticated and/or novel statistical approaches.

中文翻译：

---

质谱在全球无凝胶蛋白质组学分析中的统计应用和挑战。

通过质谱进行的全球无凝胶蛋白质组学分析已被广泛用作在整个基因组水平上探索复杂生物系统的重要工具。同时分析大量蛋白质是一项复杂而艰巨的任务。全球无凝胶蛋白质组学分析的所有阶段都面临挑战：实验设计，肽/蛋白质鉴定，数据预处理和归一化以及推论分析。除了改进分析技术的各种努力外，统计方法已应用于蛋白质组学分析的所有阶段，以帮助从大型蛋白质组学数据集中高效提取相关信息。在这篇综述中，我们总结了通过质谱技术在全球无凝胶蛋白质组学分析的几个阶段中统计学的当前应用。我们讨论了与各种统计工具的应用相关的挑战。只要有可能，我们还建议使用更复杂和/或更新颖的统计方法，针对如何改进基于质谱的全球蛋白质组学分析的数据收集和解释的潜在解决方案。