Utilizing RNA-Seq data for de novo coexpression network inference

Research output: Contribution to journalArticle

76 Citations (Scopus)

Abstract

Motivation: RNA-Seq experiments have shown great potential for transcriptome profiling. While sequencing increases the level of biological detail, integrative data analysis is also important. One avenue is the construction of coexpression networks. Because the capacity of RNA-Seq data for network construction has not been previously evaluated, we constructed a coexpression network using striatal samples, derived its network properties and compared it with microarray-based networks. Results: The RNA-Seq coexpression network displayed scalefree, hierarchical network structure. We detected transcripts groups (modules) with correlated profiles; modules overlap distinct ontology categories. Neuroanatomical data from the Allen Brain Atlas reveal several modules with spatial colocalization. The network was compared with microarray-derived networks; correlations from RNA-Seq data were higher, likely because greater sensitivity and dynamic range. Higher correlations result in higher network connectivity, heterogeneity and centrality. For transcripts present across platforms, network structure appeared largely preserved. From this study, we present the first RNA-Seq data de novo network inference.

Original languageEnglish (US)
Article numberbts245
Pages (from-to)1592-1597
Number of pages6
JournalBioinformatics
Volume28
Issue number12
DOIs
StatePublished - Jun 2012

Fingerprint

RNA
Microarrays
Corpus Striatum
Network Structure
Microarray
Module
Atlases
Gene Expression Profiling
Ontology
Brain
Hierarchical Networks
Network Connectivity
Centrality
Atlas
Scale-free Networks
Dynamic Range
Hierarchical Structure
Profiling
Sequencing
Overlap

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Computational Mathematics
  • Statistics and Probability
  • Medicine(all)

Cite this

Utilizing RNA-Seq data for de novo coexpression network inference. / Iancu, Ovidiu; Kawane, Sunita; Bottomly, Daniel; Searles, Robert; Hitzemann, Robert; McWeeney, Shannon.

In: Bioinformatics, Vol. 28, No. 12, bts245, 06.2012, p. 1592-1597.

Research output: Contribution to journalArticle

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