DOI: 10.1101/502302Dec 20, 2018Paper

Measuring rank robustness in scored protein interaction networks

BioRxiv : the Preprint Server for Biology
Lyuba V BozhilovaCharlotte M Deane

Abstract

Background: Protein interaction databases often provide confidence scores for each recorded interaction based on the available experimental evidence. Protein interaction networks (PINs) are then built by thresholding on these scores, so that only interactions of sufficiently high quality are included. These networks are used to identify biologically relevant motifs or nodes using metrics such as degree or betweenness centrality. This type of analysis can be sensitive to the choice of threshold. If a node metric is to be useful for extracting biological signal, it should induce similar node rankings across PINs obtained at different reasonable confidence score thresholds. Results: We propose three measures\---|rank continuity, identifiability, and instability\---|to evaluate how robust a node metric is to changes in the score threshold. We apply our measures to twenty-five metrics and identify four as the most robust: the number of edges in the step-1 ego network, as well as the leave-one-out differences in average redundancy, average number of edges in the step-1 ego network, and natural connectivity. Our measures show good agreement across PINs from different species and data sources. Analysis of synthetically generated scored...Continue Reading

Related Concepts

Anatomy, Regional
Surgical Incisions
Along Edge (Qualifier Value)
Evaluation
Structure
Anatomic Node
Protein-Protein Interaction
Analysis
Binding (Molecular Function)
Detection

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