ppiStats

ppiStats analyzes protein-protein interaction (PPI) datasets to assess error characteristics and quantify artifacts and stochastic error rates in large-scale bait-prey studies, with emphasis on Saccharomyces cerevisiae.

Key Features:

• Directed Graph Model for Bait-Prey Systems: Represents bait-to-prey systems as a directed graph to structure analysis of interaction networks.
• Multinomial Error Model: Implements a multinomial error model to assess error statistics and distinguish true interactions from artifacts.
• Characterization of Interaction Traits: Characterizes datasets by the set of tested interactions, artifacts leading to false positives/negatives, and estimates of stochastic error rates.

Scientific Applications:

• Protein Interactome Estimation: Supports more accurate estimation of the protein interactome by accounting for artifacts and stochastic error rates in PPI data.
• Module Characterization: Facilitates characterization of protein modules within interactomes by providing error-aware assessments of interaction data.

Methodology:

ppiStats applies a directed graph model and multinomial error modeling to systematically evaluate large-scale PPI datasets.