Package: MetNet 1.31.0

Thomas Naake

MetNet: Inferring metabolic networks from untargeted high-resolution mass spectrometry data

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.

Authors:Thomas Naake [aut, cre], Liesa Salzer [ctb], Elva Maria Novoa-del-Toro [ctb]

MetNet_1.31.0.tar.gz
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MetNet_1.31.0.tgz(r-4.6-any)MetNet_1.31.0.tgz(r-4.5-any)
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
MetNet/json (API)

# Install 'MetNet' in R:

install.packages('MetNet', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

mat_test - Example data for 'MetNet': unit tests
mat_test_z - Example data for 'MetNet': unit tests
peaklist - Example data for 'MetNet': data input
sps_sub - Spectra data to test addSpectralSimilarity
x_annotation - Example annotation for 'MetNet': data input
x_test - Example data for 'MetNet': data input

On BioConductor:MetNet-1.31.0(bioc 3.24)MetNet-1.30.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

immunooncology metabolomics massspectrometry network regression

5.40 score 1 scripts 15 mentions 21 exports 68 dependencies

Last updated from:a6b1a68bdc. Checks:1 WARNING, 7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	WARNING	240
linux-devel-x86_64	NOTE	489
source / vignettes	OK	259
linux-release-x86_64	NOTE	471
macos-release-arm64	NOTE	269
macos-oldrel-arm64	NOTE	219
windows-devel	NOTE	306
windows-release	NOTE	289
windows-oldrel	NOTE	294
wasm-release	OK	196

Exports:addSpectralSimilarity AdjacencyMatrix aracne bayes clr combine correlation directed getLinks lasso mz_summary mz_vis partialCorrelation randomForest rtCorrection show statistical structural threshold thresholded type

Dependencies:abind BH Biobase BiocGenerics BiocParallel bnlearn cli codetools corpcor cpp11 DelayedArray dplyr farver fdrtool formatR futile.logger futile.options GeneNet generics GENIE3 GenomicRanges ggplot2 glue GPArotation gtable IRanges isoband labeling lambda.r lattice lifecycle longitudinal magrittr Matrix MatrixGenerics matrixStats mnormt nlme parmigene pillar pkgconfig plyr psych purrr R6 RColorBrewer Rcpp reshape2 rlang S4Arrays S4Vectors S7 scales Seqinfo snow SparseArray stabs stringi stringr SummarizedExperiment tibble tidyr tidyselect utf8 vctrs viridisLite withr XVector

MetNet: Inferring metabolic networks from untargeted high-resolution mass spectrometry data

Rendered fromMetNet.Rmdusingknitr::rmarkdown

Last update: 2025-10-23
Started: 2019-11-07

Help page	Topics
Inferring metabolic networks from untargeted high-resolution mass spectrometry data	MetNet-package MetNet
Create S4 class AdjacencyMatrix	.AdjacencyMatrix
Check if all the assays in the `AdjacencyMatrix` object have identical colnames and rownames	.assays_have_identical_colnames_rownames
Check if the assays in the `AdjacencyMatrix` object have identical dimnames	.assays_have_identical_dimnames
Adding a spectral similarity matrix to the "structural" `AdjacencyMatrix`	addSpectralSimilarity
Add adjacency matrix to list	addToList
Wrapper to create an instance of S4 class AdjacencyMatrix	AdjacencyMatrix
Methods for `AdjacencyMatrix` objects	AdjacencyMatrix-class as.data.frame as.data.frame,AdjacencyMatrix-method dim dim,AdjacencyMatrix-method directed directed,AdjacencyMatrix-method length,AdjacencyMatrix-method show show,AdjacencyMatrix-method thresholded thresholded,AdjacencyMatrix-method type type,AdjacencyMatrix-method
Placeholder for generics functions documentation	AllGenerics
Create an adjacency matrix based on algorithm for the reconstruction of accurate cellular networks	aracne
Create an adjacency matrix based on score-based structure learning algorithm	bayes
Create an adjacency matrix based on context likelihood or relatedness network	clr
Combine structural and statistical `AdjacencyMatrix` objects	combine
Create an adjacency matrix based on correlation	correlation
Write an adjacency matrix to a `data.frame`	getLinks
Create an adjacency matrix based on LASSO	lasso
Example data for 'MetNet': unit tests	mat_test
Example data for 'MetNet': unit tests	mat_test_z
Spectra data to test addSpectralSimilarity	ms2_test sps_sub
Create a summary from adjacency list containing mass differences	mz_summary
Visualize mass difference distribution	mz_vis
Calculate the partial correlation and p-values	partialCorrelation
Example data for 'MetNet': data input	peaklist
Create an adjacency matrix based on random forest	randomForest
Correct connections in the structural adjacency matrices by retention time	rtCorrection
Spectra data to test addSpectralSimilarity	spectra_matrix
Create an `AdjacencyMatrix` object containing assays of adjacency matrices from statistical methods	statistical
Create adjacency matrix based on m/z (molecular weight) difference	structural
Threshold the statistical adjacency or spectral similarity matrices	threshold
Return consensus ranks from a matrix containing ranks	topKnet
Example annotation for 'MetNet': data input	x_annotation
Example data for 'MetNet': data input	x_test

Package: MetNet 1.31.0

MetNet: Inferring metabolic networks from untargeted high-resolution mass spectrometry data

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