SAINT: probabilistic scoring of affinity purification–mass spectrometry data - Choi, Hyungwon; Larsen, Brett; Lin, Zhen-Yuan; Breitkreutz, Ashton; Mellacheruvu, Dattatreya; Fermin, Damian; Qin, Zhaohui S; Tyers, Mike; Gingras, Anne-Claude; Nesvizhskii, Alexey I (Nature methods, 2011)
A statistical framework for assigning confidence scores for protein-protein interaction data generated via affinity purification–mass spectrometry, called significance analysis of interactome (SAINT) is described. We present 'significance analysis of interactome' (SAINT), a computational tool that assigns confidence scores to protein-protein interaction data generated using affinity purification–mass spectrometry (AP-MS). The method uses label-free quantitative data and constructs separate distributions for true and false interactions to derive the probability of a bona fide protein-protein interaction. We show that SAINT is applicable to data of different scales and protein connectivity and allows transparent analysis of AP-MS data.