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Path-level interpretation of Gaussian graphical models using the pair-path subscore.

Nathan P Gill1, Raji Balasubramanian2, James R Bain3,4,5

  • 1Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.

BMC Bioinformatics
|January 6, 2022
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We introduce the pair-path subscore (PPS) to interpret Gaussian graphical models by scoring network paths. This method quantifies path importance in determining node correlations, aiding biological network analysis.

Keywords:
Graph theoryGraphical modelsMetabolomicsNetwork analysis

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Area of Science:

  • Systems Biology
  • Bioinformatics
  • Network Analysis

Background:

  • Network construction from biological data is common, often using Gaussian graphical models.
  • Current methods focus on pairwise dependencies but struggle to interpret path contributions to network correlations.
  • Understanding subnetwork structures is crucial for biological insights.

Purpose of the Study:

  • To develop a method for interpreting Gaussian graphical models at the network path level.
  • To quantify the contribution of individual paths to the correlation between terminal nodes.
  • To enhance biological network analysis by probing finer structural details.

Main Methods:

  • Propose the pair-path subscore (PPS) method.
  • Score network paths based on their importance in determining Pearson correlation between terminal nodes.
  • Implement the method in an R package named pps.

Main Results:

  • Validated PPS using human metabolomics data from the Hyperglycemia and adverse pregnancy outcome (HAPO) study.
  • Confirmed well-documented biological relationships among metabolites.
  • Demonstrated PPS's utility in generating novel biological hypotheses through exploratory analysis.

Conclusions:

  • PPS enables detailed probing of network topology by identifying key contributing paths.
  • The method enhances understanding of marginal behavior within complex biological networks.
  • PPS expands the toolkit for network data analysis, facilitating new research questions.