MetNet

DOI:10.18129/B9.bioc.MetNet

Inferring metabolic networks from untargeted high-resolution mass spectrometry data

Bioconductor version: Release (3.16)

MetNet contains functionality to infer metabolic network topologies from quantitative data and high-resolution mass/charge information. Using statistical models (including correlation, mutual information, regression and Bayes statistics) and quantitative data (intensity values of features) adjacency matrices are inferred that can be combined to a consensus matrix. Mass differences calculated between mass/charge values of features will be matched against a data frame of supplied mass/charge differences referring to transformations of enzymatic activities. In a third step, the two levels of information are combined to form a adjacency matrix inferred from both quantitative and structure information.

Author: Thomas Naake [aut, cre], Liesa Salzer [ctb]

Maintainer: Thomas Naake

Installation

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

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

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("MetNet")

HTML	R Script	Workflow for high-resolution metabolomics data
PDF		Reference Manual
Text		NEWS

Details

biocViews	ImmunoOncology,MassSpectrometry,Metabolomics,Network,Regression,Software
Version	1.16.0
In Bioconductor since	BioC 3.8 (R-3.5) (4 years)
License	GPL (>= 3)
Depends	R (>= 4.0),S4Vectors(>= 0.28.1),SummarizedExperiment(>= 1.20.0)
Imports	bnlearn(>= 4.3),BiocParallel(>= 1.12.0),corpcor(>= 1.6.10),dplyr(>= 1.0.3),ggplot2(>= 3.3.3),GeneNet(>= 1.2.15),GENIE3(>= 1.7.0), methods (>= 3.5),parmigene(>= 1.0.2),psych(>= 2.1.6),rlang(>= 0.4.10),stabs(>= 0.6), stats (>= 3.6),tibble(>= 3.0.5),tidyr(>= 1.1.2)
LinkingTo
Suggests	BiocGenerics(>= 0.24.0),BiocStyle(>= 2.6.1),glmnet(>= 4.1-1),igraph(>= 1.1.2),knitr(>= 1.11),rmarkdown(>= 1.15),testthat(>= 2.2.1),Spectra(>= 1.4.1),MsCoreUtils(>= 1.6.0)
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Build Report

Package Archives

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

Source Package	MetNet_1.16.0.tar.gz
Windows Binary	MetNet_1.16.0.zip
macOS Binary (x86_64)	MetNet_1.16.0.tgz
macOS Binary (arm64)	MetNet_1.16.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/MetNet
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/MetNet
Bioc Package Browser	https://code.bioconductor.org/browse/MetNet/
Package Short Url	//www.andersvercelli.com/packages/MetNet/
Package Downloads Report	Download Stats