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Genes 2017, 8(10), 246; doi:10.3390/genes8100246

Pathway Enrichment Analysis with Networks

1,* , 2
and
3,*
1
College of Information Technology and Engineering, Marshall University, 1 John Marshall Dr, Huntington, WV 25755, USA
2
College of Computer and Control Engineering, Nankai University, 94 Weijin Road, Tianjin 300071, China
3
Department of Computer Science, The University of Texas at San Antonio, 1 Utsa Cir, San Antonio, TX 78249, USA
*
Authors to whom correspondence should be addressed.
Received: 27 July 2017 / Revised: 23 September 2017 / Accepted: 27 September 2017 / Published: 28 September 2017
(This article belongs to the Special Issue Integrative Genomics and Systems Medicine in Cancer)
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Abstract

Detecting associations between an input gene set and annotated gene sets (e.g., pathways) is an important problem in modern molecular biology. In this paper, we propose two algorithms, termed NetPEA and NetPEA’, for conducting network-based pathway enrichment analysis. Our algorithms consider not only shared genes but also gene–gene interactions. Both algorithms utilize a protein–protein interaction network and a random walk with a restart procedure to identify hidden relationships between an input gene set and pathways, but both use different randomization strategies to evaluate statistical significance and as a result emphasize different pathway properties. Compared to an over representation-based method, our algorithms can identify more statistically significant pathways. Compared to an existing network-based algorithm, EnrichNet, our algorithms have a higher sensitivity in revealing the true causal pathways while at the same time achieving a higher specificity. A literature review of selected results indicates that some of the novel pathways reported by our algorithms are biologically relevant and important. While the evaluations are performed only with KEGG pathways, we believe the algorithms can be valuable for general functional discovery from high-throughput experiments. View Full-Text
Keywords: pathway; protein–protein interaction network; enrichment analysis; gene sets; random walk with restart pathway; protein–protein interaction network; enrichment analysis; gene sets; random walk with restart
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Liu, L.; Wei, J.; Ruan, J. Pathway Enrichment Analysis with Networks. Genes 2017, 8, 246.

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