MRHCA: a nonparametric statistics based method for hub and co-expression module identification in large gene co-expression network

Yu Zhang, Sha Cao, Jing Zhao, Burair Alsaihati, Qin Ma, Chi Zhang

Research output: Contribution to journalArticle

Abstract

Background: Gene co-expression and differential co-expression analysis has been increasingly used to study cofunctional and co-regulatory biological mechanisms from large scale transcriptomics data sets. Methods: In this study, we develop a nonparametric approach to identify hub genes and modules in a large coexpression network with low computational and memory cost, namely MRHCA. Results: We have applied the method to simulated transcriptomics data sets and demonstrated MRHCA can accurately identify hub genes and estimate size of co-expression modules. With applying MRHCA and differential coexpression analysis to E. coli and TCGA cancer data, we have identified significant condition specific activated genes in E. coli and distinct gene expression regulatory mechanisms between the cancer types with high copy number variation and small somatic mutations. Conclusion: Our analysis has demonstrated MRHCA can (i) deal with large association networks, (ii) rigorously assess statistical significance for hubs and module sizes, (iii) identify co-expression modules with low associations, (iv) detect small and significant modules, and (v) allow genes to be present in more than one modules, compared with existing methods. [Figure not available: see fulltext.].

Original languageEnglish (US)
Pages (from-to)40-55
Number of pages16
JournalQuantitative Biology
Volume6
Issue number1
DOIs
StatePublished - Mar 1 2018

Keywords

  • Mutual Rank
  • algorithm for large scale networks analysis
  • gene co-expression network
  • statistical significance of gene co-expression

ASJC Scopus subject areas

  • Modeling and Simulation
  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • Computer Science Applications
  • Applied Mathematics

Fingerprint Dive into the research topics of 'MRHCA: a nonparametric statistics based method for hub and co-expression module identification in large gene co-expression network'. Together they form a unique fingerprint.

  • Cite this