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Mapping Dysfunctional Protein-Protein Interactions in Disease
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EPSILON: an eQTL prioritization framework using similarity measures derived from local networks.

Lieven P C Verbeke1, Lore Cloots, Piet Demeester

  • 1Department of Information Technology, Ghent University - iMinds, 9050 Gent, Belgium. lieven.verbeke@intec.ugent.be

Bioinformatics (Oxford, England)
|April 19, 2013
PubMed
Summary

EPSILON prioritizes causal genes from expression quantitative trait loci (eQTL) data by constructing local networks, outperforming existing methods. This approach improves accuracy by mitigating issues with highly connected genes in physical interaction networks.

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Area of Science:

  • Genomics
  • Systems Biology
  • Bioinformatics

Background:

  • Expression quantitative trait loci (eQTL) analysis often involves multiple candidate genes.
  • Prioritization techniques use physical interaction networks, which can be noisy and contain highly connected genes.
  • Existing methods struggle with unreliable interactions, hindering accurate causal gene identification.

Purpose of the Study:

  • To present EPSILON, an extendable framework for expression quantitative trait loci (eQTL) prioritization.
  • To mitigate the impact of highly connected genes and unreliable interactions in network-based prioritization.
  • To improve the selection of the most likely causal gene from eQTL data.

Main Methods:

  • Constructing a local network using a k-trials shortest path algorithm.
  • Applying network-based similarity measures (random walks, Laplacian Exponential Diffusion, Regularized Commute-Time kernels).
  • Evaluating prioritization performance on yeast eQTL datasets and predicting knockout interactions.

Main Results:

  • EPSILON outperformed reference methods (random assignment, shortest path prioritization).
  • Using a local network significantly increased prioritization performance compared to global networks.
  • An average increase of 8 percentage points in prioritization performance was observed (P < 10(-5)).

Conclusions:

  • EPSILON provides an effective framework for eQTL prioritization.
  • Local network construction is crucial for improving the accuracy of network-based prioritization.
  • The EPSILON approach enhances the identification of causal genes in genomic studies.