IsotopicLabelling package allows to analyse the isotopic patterns in MS data
obtained in isotopic labelling experiments. From the experimental patterns,
the package estimates the isotopic abundance of the stable isotope employed in
the labelling experiment (either ^2H or ^13C) inside a specified compound.
Given a data frame of LC-MS or GC-MS peak intensities or areas (one column for each sample to analyse),
IsotopicLabelling package first extracts the isotopic patterns of the specified compound,
and then performs an isotopic pattern analysis to estimate the isotopic abundance of the labelling isotope.
This is performed through a weighted non-linear least squares fitting procedure,
where the resulting estimate is the value for which the theoretical pattern best reproduces
the experimental one.
During the fitting, the experimental signals are given weights proportional to the square root
of their intensity, to correct for the non uniform variance at different intensity levels.
The theoretical patterns are computed using the
ecipex R package.
The isotopic pattern analysis can be divided into the following steps:
Starting from a class
xcmsSet object (from the
xcms R package),
generate a data frame of peak signal intensities or areas,
with each column corresponding to a sample.
This step can be avoided if the data frame is already available (obtained by other means);
Extract from the data frame the experimental isotopic patterns of the specified compound (one pattern for each sample). In the chemical formula of the compound, the element whose abundance is unknown is called "X";
Normalise the patterns and estimate the abundance of the label through a weighted non-linear least squares fitting procedure.
Summarize the results.
Ruggero Ferrazza, Pietro Franceschi
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