rMSIannotation: A peak annotation tool for mass spectrometry imaging based on the analysis of isotopic intensity ratios.

Analytica Chimica Acta
Lluc SementéPere Ràfols

Abstract

Mass spectrometry imaging (MSI) consist of spatially located spectra with thousands of peaks. Only a fraction of these peaks corresponds to unique monoisotopic peaks, as mass spectra include isotopes, adducts and fragments of compounds. Current peak annotation solutions depend on matching MS features to compounds libraries. We present rMSIannotation, a peak annotation algorithm to annotate carbon isotopes and adducts in metabolomics and lipidomics imaging mass spectrometry datasets without using supporting libraries. rMSIannotation measures and evaluates the intensity ratio between carbon isotopic peaks and models their distribution across the m/z axis of the compounds in the Human Metabolome Database. Monoisotopic peak selection is based on the isotopic likelihood score (ILS) made of three components: image morphology correlation, validation of isotopic intensity ratios, and peak centroid mass deviation. rMSIannotation proposes pairs of peaks that can be adducts based on three scores: isotopic pattern coherence, image correlation and mass error. We validated rMSIannotation with three MALDI-MSI datasets which were manually annotated by experts, and compared the annotations obtained with rMSIannotation and with the METASPACE ann...Continue Reading

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