predictionet: Inference for predictive networks designed for (but not limited to) genomic data

This package contains a set of functions related to network inference combining genomic data and prior information extracted from biomedical literature and structured biological databases. The main function is able to generate networks using Bayesian or regression-based inference methods; while the former is limited to < 100 of variables, the latter may infer networks with hundreds of variables. Several statistics at the edge and node levels have been implemented (edge stability, predictive ability of each node, ...) in order to help the user to focus on high quality subnetworks. Ultimately, this package is used in the 'Predictive Networks' web application developed by the Dana-Farber Cancer Institute in collaboration with Entagen.

Install the latest version of this package by entering the following in R:
source("https://bioconductor.org/biocLite.R")
biocLite("predictionet")
AuthorBenjamin Haibe-Kains, Catharina Olsen, Gianluca Bontempi, John Quackenbush
Bioconductor views GraphAndNetwork NetworkInference
Date of publicationNone
MaintainerBenjamin Haibe-Kains <bhaibeka@jimmy.harvard.edu>, Catharina Olsen <colsen@ulb.ac.be>
LicenseArtistic-2.0
Version1.20.0
http://compbio.dfci.harvard.edu
http://www.ulb.ac.be/di/mlg

View on Bioconductor

Functions

adj.get.hops Man page
adj.remove.cycles Man page
annot2.ras Man page
annot.ras Man page
data2.ras Man page
data.discretize Man page
data.ras Man page
demo2.ras Man page
demo.ras Man page
eval.network Man page
expO.colon.ras Man page
jorissen.colon.ras Man page
mcc Man page
net2pred Man page
netinf Man page
netinf2gml Man page
netinf.cv Man page
netinf.predict Man page
predictionet Man page
predictionet-package Man page
predictionet.press.statistic Man page
predictionet.stability.cv Man page
pred.score Man page
priors2.ras Man page
priors.ras Man page

Files

.BBSoptions
DESCRIPTION
NAMESPACE
R
R/adj.get.hops.R R/adj.remove.cycles.R R/build.regression.regrnet.R R/build2.mim.R R/data.discretize.R R/eval.network.R R/exportGML.R R/extract.adjacency.ensemble.R R/extract.all.parents.R R/fit.catnet.R R/fit.regrnet.causal.R R/fit.regrnet.causal.ensemble.R R/fit.regrnet.causal2.R R/get.ii4triplets.gaussian.R R/list2matrixens.R R/mcc.R R/net2pred.R R/netinf.R R/netinf.cv.R R/netinf.predict.R R/netinf2gml.R R/network2triplets.R R/pred.onegene.bayesnet.fs.R R/pred.onegene.regrnet.fs.R R/pred.score.R R/pred2mean.R R/predictionet.press.statistic.R R/predictionet.stability.cv.R R/rank.genes.causal.ensemble.R R/rank.genes.causal.perturbations.R R/rank.genes.causal.perturbations2.R R/rank.genes.ensemble.R R/regrlin.R R/regrnet2matrixtopo.R R/stab.cv2stab.R R/topo2stab.R
README
build
build/predictionet.pdf
build/vignette.rds
data
data/datalist
data/expO.colon.ras.rda
data/jorissen.colon.ras.rda
inst
inst/doc
inst/doc/predictionet.R
inst/doc/predictionet.Rnw
inst/doc/predictionet.pdf
inst/extdata
inst/extdata/bild2006_ras_signature_348.csv
inst/extdata/preditionet_vizmap1.props
inst/extdata/preditionet_vizmap2.props
inst/extdata/priors_ras_bild2006_pnwebapp.csv
man
man/adj.get.hops.Rd man/adj.remove.cycles.Rd man/data.discretize.Rd man/eval.network.Rd man/expO.colon.ras.Rd man/jorissen.colon.ras.Rd man/mcc.Rd man/net2pred.Rd man/netinf.Rd man/netinf.cv.Rd man/netinf.predict.Rd man/netinf2gml.Rd man/pred.score.Rd man/predictionet-package.Rd man/predictionet.press.statistic.Rd man/predictionet.stability.cv.Rd
src
src/foo_mrmr.cpp
src/foo_mrmr.h
src/mrnet_adapted.cpp
src/mrnet_adapted2.cpp
src/mrnet_ensemble_standalone.cpp
src/tree.h
vignettes
vignettes/biblio.bib
vignettes/predictionet-cytoscape.pdf
vignettes/predictionet-pn_webapp_ras.pdf
vignettes/predictionet-regrnet_design.pdf
vignettes/predictionet.Rnw

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.