Introduction

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.

Publications

  1. SAINT: probabilistic scoring of affinity purification-mass spectrometry data.
    Cite this
    Choi H, Larsen B, Lin ZY, Breitkreutz A, Mellacheruvu D, Fermin D, Qin ZS, Tyers M, Gingras AC, Nesvizhskii AI, 2011-01-01 - Nature methods

Credits

  1. Hyungwon Choi
    Developer

    Department of Pathology, University of Michigan, United States of America

  2. Brett Larsen
    Developer

  3. Zhen-Yuan Lin
    Developer

  4. Ashton Breitkreutz
    Developer

  5. Dattatreya Mellacheruvu
    Developer

  6. Damian Fermin
    Developer

  7. Zhaohui S Qin
    Developer

  8. Mike Tyers
    Developer

  9. Anne-Claude Gingras
    Developer

  10. Alexey I Nesvizhskii
    Investigator

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Summary
AccessionBT002748
Tool TypeApplication
Category
PlatformsWindows
TechnologiesC
User InterfaceTerminal Command Line
Download Count0
Submitted ByAlexey I Nesvizhskii