Modeling contaminants in AP-MS/MS experiments.

ABSTRACT: Identification of protein-protein interactions (PPI) by affinity purification (AP) coupled with tandem mass spectrometry (AP-MS/MS) produces large data sets with high rates of false positives. This is in part because of contamination at the AP level (due to gel contamination, nonspecific binding to the TAP columns in the context of tandem affinity purification, insufficient purification, etc.). In this paper, we introduce a Bayesian approach to identify false-positive PPIs involving contaminants in AP-MS/MS experiments. Specifically, we propose a confidence assessment algorithm (called Decontaminator) that builds a model of contaminants using a small number of representative control experiments. It then uses this model to determine whether the Mascot score of a putative prey is significant

SUBMITTER: Lavallee-Adam M 

PROVIDER: S-EPMC4494835 | biostudies-literature | 2011 Feb

REPOSITORIES: biostudies-literature