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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.:
A detailed description of best practice usage may be found in the publication https://link.springer.com/protocol/10.1007/978-1-4939-7819-9_20.
You can install the development version of MetabolomicsBasics from GitHub with:
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)
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.