SAINT: Probabilistic Scoring of Affinity Purification-mass Spectrometry Data

Overview

Journal Nat Methods

Specialties Biomedical Engineering
Pathology

Date 2010 Dec 7

PMID 21131968

Citations 413

Authors

Hyungwon Choi

Brett Larsen

Zhen-Yuan Lin

Ashton Breitkreutz

Dattatreya Mellacheruvu

Damian Fermin

Zhaohui S Qin

Mike Tyers

Anne-Claude Gingras

Alexey I Nesvizhskii

Affiliations

Soon will be listed here.

Abstract

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.

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