famat

DOI: 10.18129/B9.bioc.famat    

This is the development version of famat; for the stable release version, see famat.

Functional analysis of metabolic and transcriptomic data

Bioconductor version: Development (3.14)

Famat is made to collect data about lists of genes and metabolites provided by user, and to visualize it through a Shiny app. Information collected is: - Pathways containing some of the user's genes and metabolites (obtained using a pathway enrichment analysis). - Direct interactions between user's elements inside pathways. - Information about elements (their identifiers and descriptions). - Go terms enrichment analysis performed on user's genes. The Shiny app is composed of: - information about genes, metabolites, and direct interactions between them inside pathways. - an heatmap showing which elements from the list are in pathways (pathways are structured in hierarchies). - hierarchies of enriched go terms using Molecular Function and Biological Process.

Author: Emilie Secherre <emisecherre at gmail.com>

Maintainer: <>

Citation (from within R, enter citation("famat")):

Installation

To install this package, start R (version "4.1") and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("famat")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

PDF   Reference Manual

Details

biocViews FunctionalPrediction, GO, GeneSetEnrichment, KEGG, Pathways, Reactome, Software
Version 1.3.0
In Bioconductor since BioC 3.12 (R-4.0) (0.5 years)
License GPL-3
Depends R (>= 4.0)
Imports KEGGREST, MPINet, dplyr, gprofiler2, rWikiPathways, reactome.db, stringr, GO.db, ontologyIndex, tidyr, shiny, shinydashboard, shinyBS, plotly, magrittr, DT, clusterProfiler, org.Hs.eg.db
LinkingTo
Suggests BiocStyle, knitr, rmarkdown, testthat, BiocManager
SystemRequirements
Enhances
URL https://github.com/emiliesecherre/famat
BugReports https://github.com/emiliesecherre/famat/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package
Windows Binary
macOS 10.13 (High Sierra)
Source Repository git clone https://git.bioconductor.org/packages/famat
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/famat
Package Short Url https://bioconductor.org/packages/famat/
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