minet: A R/Bioconductor package for inferring large transcriptional networks using mutual information

BMC Bioinformatics. 2008 Oct 29;9:461. doi: 10.1186/1471-2105-9-461.


Results: This paper presents the R/Bioconductor package minet (version 1.1.6) which provides a set of functions to infer mutual information networks from a dataset. Once fed with a microarray dataset, the package returns a network where nodes denote genes, edges model statistical dependencies between genes and the weight of an edge quantifies the statistical evidence of a specific (e.g transcriptional) gene-to-gene interaction. Four different entropy estimators are made available in the package minet (empirical, Miller-Madow, Schurmann-Grassberger and shrink) as well as four different inference methods, namely relevance networks, ARACNE, CLR and MRNET. Also, the package integrates accuracy assessment tools, like F-scores, PR-curves and ROC-curves in order to compare the inferred network with a reference one.

Conclusion: The package minet provides a series of tools for inferring transcriptional networks from microarray data. It is freely available from the Comprehensive R Archive Network (CRAN) as well as from the Bioconductor website.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Computational Biology / methods*
  • Data Interpretation, Statistical
  • False Positive Reactions
  • Gene Expression Profiling / methods
  • Internet
  • Models, Statistical
  • Oligonucleotide Array Sequence Analysis
  • Pattern Recognition, Automated / methods
  • Programming Languages
  • ROC Curve
  • Reproducibility of Results
  • Software
  • Transcription, Genetic