famat

DOI:10.18129/B9.bioc.famat

Functional analysis of metabolic and transcriptomic data

Bioconductor version: Release (3.16)

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: Mathieu Charles [aut, cre]

Maintainer: Mathieu Charles

Installation

To install this package, start R (version "4.2") and enter:

if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("famat")

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

Documentation

查看文档的版本包age installed in your system, start R and enter:

browseVignettes("famat")

HTML	R Script	famat
PDF		Reference Manual
Text		NEWS

Details

biocViews	FunctionalPrediction,GO,GeneSetEnrichment,KEGG,Pathways,Reactome,Software
Version	1.8.0
In Bioconductor since	BioC 3.12 (R-4.0) (2 years)
License	GPL-3
Depends	R (>= 4.0)
Imports	KEGGREST,mgcv, stats,BiasedUrn,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

Follow2021年欧洲杯比分预测 instructions to use this package in your R session.

Source Package	famat_1.8.0.tar.gz
Windows Binary	famat_1.8.0.zip
macOS Binary (x86_64)	famat_1.8.0.tgz
macOS Binary (arm64)	famat_1.8.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/famat
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/famat
Bioc Package Browser	https://code.bioconductor.org/browse/famat/
Package Short Url	//www.andersvercelli.com/packages/famat/
Package Downloads Report	Download Stats