GitHub - janlisec/MetabolomicsBasics: Basic Functions to Investigate Metabolomics Data Matrices (original) (raw)

MetabolomicsBasics

The goal of MetabolomicsBasics is to provide a set of functions to investigate raw data (a matrix of intensity values) from (metabol)omics experiments, i.e. following peak picking and signal deconvolution. Functions can be used to i.e.:

• normalize data
• detect biomarkers
• perform sample classification

A detailed description of best practice usage may be found in the publicationhttps://link.springer.com/protocol/10.1007/978-1-4939-7819-9_20.

Installation

You can install the development version of MetabolomicsBasics fromGitHub with:

install.packages("devtools")

devtools::install_github("janlisec/MetabolomicsBasics")

Examples

A typical use case would be to compute a Principal Component Analysis:

raw <- MetabolomicsBasics::raw sam <- MetabolomicsBasics::sam MetabolomicsBasics::RestrictedPCA(dat = raw, sam = sam, group.col = "Group", legend.x = "bottomleft", medsd = TRUE, fmod = "Group")

More elaborate plots, like the polar coordinate visualization of heterosis pattern are possible:

x <- t(raw) colnames(x) <- sam$GT MetabolomicsBasics::PolarCoordHeterPlot(x=x, gt=c("B73","B73xMo17","Mo17"), plot_lab="graph", col=1:10, thr=0.5, rev_log=exp(1)) #> Parameter 'col' should be a color vector of length nrow(x)