Imports: Rcpp (>= 1.0.1), Rdpack, dplyr, tibble, stats, methods, curl,
Suggests: testthat (>= 2.1.0), knitr, rmarkdown, readr, bc3net,
corpcor, DWLasso, GENIE3, huge, igraph, minet, ggplot2, SeqNet,

Imports: Rcpp (>= 1.0.1), biomaRt, reactome.db, corpcor, igraph,
ggplot2, SeqNet, Rdpack, dplyr, tibble, stats, methods, curl,

Imports: Rcpp (>= 1.0.1), biomaRt, corpcor, igraph, ggplot2, SeqNet,
Rdpack, dplyr, tibble, stats, methods, curl, graphics,
DWLasso, huge, GENIE3, minet, reactome.db

dplyr, tibble, stats, methods, curl, graphics, grDevices,

Description: Community detection for dynamic networks, i.e., networks measured repeatedly over a sequence of discrete time points, using a latent space approach.
Imports: Rcpp (>= 0.12.4), igraph, MCMCpack, vegan, skmeans, plot3D,
plot3Drgl, BayesLogit, movMF, tcltk, stats, grDevices, graphics
Packaged: 2016-05-14 19:51:39 UTC; daniel-admin

Packaged: 2016-05-16 22:06:35 UTC; daniel-admin

Title: DNET: dynamic networks via an integrative analysis of biological
networks and high-throughput digitised data
Description: The 'dnet' package is initiated to fill in the need of an open-source tool for analysing biological networks and high-throughput biological data in an integrative manner. More specifically, dnet intends to analyse the biological network whose nodes/genes are associated with digitised information such as expression levels across samples. Also, dnet aims to deliver an eye-intuitive tool for network-based sample stratifications.
Collate: 'dGSEA.r' 'dGSEAview.r' 'dGSEAwrite.r' 'visGSEA.r'

Title: Dynamic NETworks via integrative analysis of digitised data in
terms of network, ontology and evolution
Description: The 'dnet' package is initiated to fill in the need of an open-source tool for digitised data in an integrative manner. More specifically, dnet intends to analyse the biological network whose nodes/genes are associated with digitised information such as expression levels across samples. To help make sense of identified networks, enrichment analysis is also supported using a wide variety of pre-compiled ontologies and phylostratific age information in major organisms including human, mouse, rat, chicken, C.elegans, fruit fly, zebrafish and arabidopsis. In summary, dnet aims to deliver an eye-intuitive tool with rich visuals but less inputs.