Choi Hyungwon, Liu Guomin, Mellacheruvu Dattatreya, Tyers Mike, Gingras Anne-Claude, Nesvizhskii Alexey I
Saw Swee Hock School of Public Health, National University of Singapore, Singapore.
Center for Systems Biology, Samuel Lunenfeld Research Institute at Mount Sinai Hospital, Toronto, Ontario, Canada.
Curr Protoc Bioinformatics. 2012 Sep;Chapter 8:8.15.1-8.15.23. doi: 10.1002/0471250953.bi0815s39.
Significance Analysis of INTeractome (SAINT) is a software package for scoring protein-protein interactions based on label-free quantitative proteomics data (e.g., spectral count or intensity) in affinity purification-mass spectrometry (AP-MS) experiments. SAINT allows bench scientists to select bona fide interactions and remove nonspecific interactions in an unbiased manner. However, there is no 'one-size-fits-all' statistical model for every dataset, since the experimental design varies across studies. Key variables include the number of baits, the number of biological replicates per bait, and control purifications. Here we give a detailed account of input data format, control data, selection of high-confidence interactions, and visualization of filtered data. We explain additional options for customizing the statistical model for optimal filtering in specific datasets. We also discuss a graphical user interface of SAINT in connection to the LIMS system ProHits, which can be installed as a virtual machine on Mac OS X or Windows computers.
相互作用组显著性分析（SAINT）是一个软件包，用于在亲和纯化-质谱（AP-MS）实验中，基于无标记定量蛋白质组学数据（如光谱计数或强度）对蛋白质-蛋白质相互作用进行评分。SAINT使实验科学家能够以无偏见的方式选择真实的相互作用并去除非特异性相互作用。然而，由于不同研究的实验设计各不相同，不存在适用于每个数据集的“一刀切”统计模型。关键变量包括诱饵数量、每个诱饵的生物学重复数量以及对照纯化。在这里，我们详细介绍输入数据格式、对照数据、高可信度相互作用的选择以及过滤后数据的可视化。我们解释了为在特定数据集中进行最佳过滤而定制统计模型的其他选项。我们还讨论了与LIMS系统ProHits相关的SAINT图形用户界面，该界面可以作为虚拟机安装在Mac OS X或Windows计算机上。
