Skip to contents

Missing compounds recovery: fits a general model (all the compounds above a certain minimum number of samples) to all the samples.

Usage

recMissComp(Experiment, min.samples, free.model = F)

# S4 method for MetaboSet
recMissComp(Experiment, min.samples, free.model = F)

Arguments

Experiment

A 'MetaboSet' S4 object containing the experiment data previously created by newExp, deconvolved by deconvolveComp and aligned by alignComp.

min.samples

The minimum number of samples in which a compound has to appear to be considered for searching into the rest of the samples where this compound missing.

free.model

If TRUE, the spectra found in the samples where the compound is missing is used to get the final average spectra. (See details)

Value

The function returns an updated S4 'MetaboSet' class, where the GC-MS samples have been now aligned.

Details

WARNING: If compounds were previously identified, they have to be identified again after applying the "recMissComp" function. This means that "identifyComp" function has to be executed always after "recMissComp" for identification of compounds, even if "identifyComp" has been previously applied before.

The free.model parameter is recomended to be always FALSE (except for carbon tracking applications). This is because the spectra of the samples where the compound is missing is usually affected by noise, and this could decrease the matching score for a certain compound.

References

[1] Domingo-Almenara X, et al. Compound deconvolution in GC-MS-based metabolomics by blind source separation. Journal of Chromatography A (2015). Vol. 1409: 226-233. DOI: 10.1016/j.chroma.2015.07.044

Author

Xavier Domingo-Almenara. xavier.domingo@urv.cat