# Inferring metabolic networks from untargeted high-resolution mass spectrometry data

## Documentation for package ‘MetNet’ version 1.6.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

MetNet-package | Inferring metabolic networks from untargeted high-resolution mass spectrometry data
addToList | Add adjacency matrix to list
aracne | Create an adjacency matrix based on algorithm for the reconstruction of accurate cellular networks
bayes | Create an adjacency matrix based on score-based structure learning algorithm
clr | Create an adjacency matrix based on context likelihood or relatedness network
combine | Combine structural and statistical adjacency matrix
correlation | Create an adjacency matrix based on correlation
getLinks | Write an adjacency matrix to a 'data.frame'
lasso | Create an adjacency matrix based on LASSO
mat_test | Example data for 'MetNet': unit tests
mat_test_z | Example data for 'MetNet': unit tests
MetNet | Inferring metabolic networks from untargeted high-resolution mass spectrometry data
peaklist | Example data for 'MetNet': data input
randomForest | Create an adjacency matrix based on random forest
rtCorrection | Correct connections in the structural adjacency matrix by retention time
statistical | Create a list of adjacency matrices from statistical methods
structural | Create adjacency matrix based on m/z (molecular weight) difference
threeDotsCall | Check if passed arguments match the function's formal arguments and call the function with the checked arguments
threshold | Threshold the statistical adjacency matrices
topKnet | Return consensus ranks from a matrix containing ranks
x_test | Example data for 'MetNet': data input