Signed network propagation for detecting differential gene expressions and DNA copy number variations

Wei Zhang, Nicholas Johnson, Baolin Wu, Rui Kuang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

Network propagation algorithms have proved useful for the analysis of high-dimensional genomic data. One limitation is that the current formulation only allows network propagation on positively weighted graphs. In this paper, we explore two signed network propagation algorithms and general optimization frameworks for detecting differential gene expressions and DNA copy number variations (CNV). The proposed algorithms consider both positive and negative relations in graphs to model gene up/down-regulation or amplification/deletion CNV events. The first algorithm (Signed-NP) integrates gene co-expressions and differential expressions for consistent and robust gene selection from microarray datasets by propagation on gene correlation graphs. The second algorithm (Signed-NPBi) identifies gene or CNV markers by propagation on sample-feature bipartite graphs to capture bi-clusters between samples and genomic features. Large scale experiments on several microarray gene expression datasets and CNV datasets validate that Signed-NP and Signed-NPBi perform better classification of gene expression and CNV data than standard network propagation. The experiments also demonstrate that Signed-NP is capable of selecting genes that are more biologically interpretable and consistent across multiple datasets, and Signed-NPBi can detect hidden CNV patterns in bi-clusters by smoothing on correlations between adjacent probes.

Original languageEnglish (US)
Title of host publication2012 ACM Conference on Bioinformatics, Computational Biology and Biomedicine, BCB 2012
Pages337-344
Number of pages8
DOIs
StatePublished - 2012
Event2012 ACM Conference on Bioinformatics, Computational Biology and Biomedicine, BCB 2012 - Orlando, FL, United States
Duration: Oct 7 2012Oct 10 2012

Publication series

Name2012 ACM Conference on Bioinformatics, Computational Biology and Biomedicine, BCB 2012

Other

Other2012 ACM Conference on Bioinformatics, Computational Biology and Biomedicine, BCB 2012
CountryUnited States
CityOrlando, FL
Period10/7/1210/10/12

Keywords

  • DNA copy number variation
  • Gene expression
  • Graph-based learning
  • Network propagation
  • Signed network

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  • Cite this

    Zhang, W., Johnson, N., Wu, B., & Kuang, R. (2012). Signed network propagation for detecting differential gene expressions and DNA copy number variations. In 2012 ACM Conference on Bioinformatics, Computational Biology and Biomedicine, BCB 2012 (pp. 337-344). (2012 ACM Conference on Bioinformatics, Computational Biology and Biomedicine, BCB 2012). https://doi.org/10.1145/2382936.2382979