SAINT: probabilistic scoring of affinity purification-mass spectrometry data.
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.
Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA.
Hyungwon
H
Choi
Brett
B
Larsen
Zhen-Yuan
ZY
Lin
Ashton
A
Breitkreutz
Dattatreya
D
Mellacheruvu
Damian
D
Fermin
Zhaohui S
ZS
Qin
Mike
M
Tyers
Anne-Claude
AC
Gingras
Alexey I
AI
Nesvizhskii
D002846:Chromatography, Affinity / Q000379:methods*; D019295:Computational Biology; D003198:Computer Simulation; D013058:Mass Spectrometry; D011336:Probability; D011485:Protein Binding; D025941:Protein Interaction Mapping / Q000379:methods*; D011506:Proteins / Q000302:isolation & purification / Q000378:metabolism*
D011506:Proteins