MetCirc: Navigating mass spectral similarity in high-resolution MS/MS metabolomics data
One of the main problems in MS/MS metabolomics is the rapid dereplication of
previously characterized metabolites across a range of biological samples and
the structural prediction of unknowns from MS/MS data. MetCirc aims to
faciliate these steps by offering functionalities to display,
(interactively) explore similarities and annotate features of MS/MS metabolomics
data. The R package is especially designed to
improve the interactive exploration of metabolomics data obtained from
cross-species/cross-tissues comparative experiments. Notably, MetCirc
includes functions to calculate the similarity between individual MS/MS
spectra based on a normalised dot product calculation taking into account
shared fragments or main neutral losses.
MetCirc: Navigating mass spectral similarity in high-resolution MS/MS metabolomics data
One of the main problems in MS/MS metabolomics is the rapid dereplication of previously characterized metabolites across a range of biological samples and the structural prediction of unknowns from MS/MS data.
MetCircaims to faciliate these steps by offering functionalities to display, (interactively) explore similarities and annotate features of MS/MS metabolomics data. TheRpackage is especially designed to improve the interactive exploration of metabolomics data obtained from cross-species/cross-tissues comparative experiments. Notably,MetCircincludes functions to calculate the similarity between individual MS/MS spectra based on a normalised dot product calculation taking into account shared fragments or main neutral losses.To install
MetCircfrom this GitHub page enter:library(devtools)install_github(repo = "PlantDefenseMetabolism/MetCirc")MetCircis also available via the Bioconductor framework. To installMetCircfrom Bioconductor enter:source("https://bioconductor.org/biocLite.R")biocLite("MetCirc")