RTNduals-package {RTNduals}R Documentation

RTNduals: An R/Bioconductor package for analysis of co-regulation and inference of 'dual regulons'.

Description

RTNduals is a tool that searches for possible co-regulatory loops between regulon pairs generated by the RTN package. It compares the shared targets in order to infer 'dual regulons', a new concept that tests whether regulators can co-operate or compete in influencing targets.

Details

Package: RTNduals
Type: Package
Depends: R (>= 3.5.0), methods, RTN (>= 2.4.2)
Imports: grDevices, stats, utils
Suggests: knitr, rmarkdown, BiocStyle, RUnit, BiocGenerics
License: Artistic-2.0
biocViews: NetworkInference, NetworkEnrichment, GeneRegulation, GeneExpression, GraphAndNetwork

Index

MBR-class: an S4 class for co-regulation analysis and inference of 'dual regulons'.
mbrPreprocess: a preprocessing function for objects of class MBR.
mbrPermutation: inference of transcriptional networks.
mbrBootstrap: inference of consensus transcriptional networks.
mbrDpiFilter: a filter based on the Data Processing Inequality (DPI) algorithm.
mbrAssociation: motifs analysis and inference of "dual regulons".
mbrPriorEvidenceTable: adds external evidences to "dual regulons".
mbrPlotDuals: plot shared targets between regulons.
mbrPlotInteraction: plots interaction effects between continuous variables.
tni2mbrPreprocess: a preprocessing function for objects of class MBR.

Further information is available in the vignettes by typing vignette("RTNduals"). Documented topics are also available in HTML by typing help.start() and selecting the RTNduals package from the menu.

Author(s)

Vinicius S. Chagas, Clarice S. Groeneveld, Kerstin B Meyer, Gordon Robertson, Mauro A. A. Castro

References

Fletcher M.N.C. et al., Master regulators of FGFR2 signalling and breast cancer risk. Nature Communications, 4:2464, 2013.

Castro M.A.A. et al., Regulators of genetic risk of breast cancer identified by integrative network analysis. Nature Genetics, 48:12-21, 2016.


[Package RTNduals version 1.4.4 Index]