ViSEAGO {ViSEAGO} | R Documentation

## ViSEAGO package

### Description

Easier data mining of biological functions organized into clusters using Gene Ontology and semantic.

### Details

The main objective of ViSEAGO workflow is to carry out a data mining of biological functions and establish links between genes involved in the study. We developed ViSEAGO in R to facilitate functional Gene Ontology (GO) analysis of complex experimental design with multiple comparisons of interest.

It allows to study large-scale datasets together and visualize GO profiles to capture biological knowledge. The acronym stands for three major concepts of the analysis: Visualization, Semantic similarity and Enrichment Analysis of Gene Ontology (`pkgdiagram`).

It provides access to the last current GO annotations (`annotate`), which are retrieved from one of NCBI EntrezGene (`Bioconductor2GO`, `EntrezGene2GO`), Ensembl (`Ensembl2GO`) or Uniprot (`Uniprot2GO`) databases for available species (`available_organisms`).

ViSEAGO extends classical functional GO analysis (`create_topGOdata`) to focus on functional coherence by aggregating closely related biological themes while studying multiple datasets at once (`merge_enrich_terms`).

It provides both a synthetic and detailed view using interactive functionalities respecting the GO graph structure (`MDSplot`, `GOterms_heatmap`, `GOclusters_heatmap`), and ensuring functional coherence supplied by semantic similarity (`build_GO_SS`, `compute_SS_distances`).

ViSEAGO has been successfully applied on several datasets from different species with a variety of biological questions. Results can be easily shared between bioinformaticians and biologists, enhancing reporting capabilities while maintaining reproducibility.

[Package ViSEAGO version 1.2.0 Index]