Imports: graph, Rgraphviz, Matrix, Biobase
Description: The 'dnet' package is initiated to fill in the need of an open-source tool for digitised data in an integrative manner in terms of network, ontology and evolution. 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.

Title: Integrative Analysis of Omics Data in Terms of Network,
Suggests: limma, survival, foreach, doParallel
Description: The focus of the dnet is to make sense of omics data (such as gene expression and mutations) from different angles including: integration with molecular networks, enrichments using ontologies, and relevance to gene evolutionary ages. Integration is achieved to identify a gene subnetwork from the whole gene network whose nodes/genes are labelled with informative data (such as the significant levels of differential expression or survival risks). To help make sense of identified gene networks, enrichment analysis is also supported using a wide variety of pre-compiled ontologies and phylostratific gene age information in major organisms including: human, mouse, rat, chicken, C.elegans, fruit fly, zebrafish and arabidopsis. Add-on functionalities are supports for calculating semantic similarity between ontology terms (and between genes) and for calculating network affinity based on random walk; both can be done via high-performance parallel computing.

Title: Integrative analysis of digitised data in terms of network,

Title: an open-source R package for omics data integrative analysis in
terms of network, evolution and ontology
Suggests: limma, survival, foreach, doMC
Description: The 'dnet' package is initiated to fill in the need of an open-source tool for high-throughput omics data in an integrative manner in terms of network, evolution and ontology. 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 gene age information in major organisms including human, mouse, rat, chicken, C.elegans, fruit fly, zebrafish and arabidopsis. Add-on functionalities are supports for semantic similarity calculation between ontology terms (and genes), and network affinity calculation using Random Walk with Restart; both can be done via high-performance parallel computing. In summary, dnet aims to deliver an eye-intuitive tool with rich visuals but less inputs.