Shotgun assays are widely used in biotechnologies to characterize large molecules, which are hard to be measured as a whole directly. For instance, in Liquid Chromatography – Mass Spectrometry (LC-MS) shotgun experiments, proteins in biological samples are digested into peptides, and then peptides are separated and measured. However, in proteomics study, investigators are usually interested in the performance of the whole proteins instead of those peptide fragments. In light of meta-analysis, we propose an adaptive thresholding method to select informative peptides, and combine peptide-level models to protein-level analysis. The meta-analysis procedure and modeling rationale can be adapted to data analysis of other types of shotgun assays.

中文翻译：

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肽的 Meta 分析以检测蛋白质的重要​​性

霰弹枪分析广泛用于生物技术中来表征难以直接作为整体测量的大分子。例如，在液相色谱-质谱 (LC-MS) 鸟枪实验中，生物样品中的蛋白质被消化成肽，然后肽被分离和测量。然而，在蛋白质组学研究中，研究人员通常对整个蛋白质而不是那些肽片段的性能感兴趣。根据荟萃分析，我们提出了一种自适应阈值方法来选择信息肽，并将肽水平模型与蛋白质水平分析相结合。元分析程序和建模原理可适用于其他类型的鸟枪法的数据分析。