Teo Guoci, Liu Guomin, Zhang Jianping, Nesvizhskii Alexey I, Gingras Anne-Claude, Choi Hyungwon
Department of Statistics and Applied Probability, National University of Singapore, Singapore.
Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada.
J Proteomics. 2014 Apr 4;100:37-43. doi: 10.1016/j.jprot.2013.10.023. Epub 2013 Oct 26.
Significance Analysis of INTeractome (SAINT) is a statistical method for probabilistically scoring protein-protein interaction data from affinity purification-mass spectrometry (AP-MS) experiments. The utility of the software has been demonstrated in many protein-protein interaction mapping studies, yet the extensive testing also revealed some practical drawbacks. In this paper, we present a new implementation, SAINTexpress, with simpler statistical model and quicker scoring algorithm, leading to significant improvements in computational speed and sensitivity of scoring. SAINTexpress also incorporates external interaction data to compute supplemental topology-based scores to improve the likelihood of identifying co-purifying protein complexes in a probabilistically objective manner. Overall, these changes are expected to improve the performance and user experience of SAINT across various types of high quality datasets.
We present SAINTexpress, an upgraded implementation of Significance Analysis of INTeractome (SAINT) for filtering high confidence interaction data from affinity purification-mass spectrometry (AP-MS) experiments. SAINTexpress features faster computation and incorporation of external data sources into the scoring, improving the performance and user experience of SAINT across various types of datasets. This article is part of a Special Issue entitled: Can Proteomics Fill the Gap Between Genomics and Phenotypes?
相互作用组显著性分析（SAINT）是一种用于对来自亲和纯化-质谱（AP-MS）实验的蛋白质-蛋白质相互作用数据进行概率评分的统计方法。该软件的实用性已在许多蛋白质-蛋白质相互作用图谱研究中得到证明，但广泛的测试也揭示了一些实际缺点。在本文中，我们提出了一种新的实现方式SAINTexpress，它具有更简单的统计模型和更快的评分算法，从而在计算速度和评分灵敏度方面有显著提高。SAINTexpress还整合了外部相互作用数据以计算基于拓扑结构的补充分数，从而以概率客观的方式提高识别共纯化蛋白质复合物的可能性。总体而言，这些变化有望改善SAINT在各种高质量数据集上的性能和用户体验。
我们展示了SAINTexpress，这是相互作用组显著性分析（SAINT）的升级版，用于从亲和纯化-质谱（AP-MS）实验中筛选高可信度的相互作用数据。SAINTexpress的特点是计算速度更快，并将外部数据源纳入评分，从而改善了SAINT在各种类型数据集上的性能和用户体验。本文是名为《蛋白质组学能否填补基因组学与表型之间的空白？》的特刊的一部分。
