In my lipid metabolomics raw data, some of metabolites only appear in negative ion identification data, while some can be detected under both ion mode. I wonder if I can pick differential metabolites from them both. Some studies seem to display data from either one mode, and some display both mode results separately. I know that data from different ion mode can't be compared together, but can I just pick them for an overview of differential metabolites between 2 groups? What about your opinion?
Yes, you can definitely combine both modes to find total differential metabolites as long as you have MS/MS and RT matrix for all of them as sole MS1 are not helpful for amy downstream identification. Also take a look at MS-FLO from C Davis Fien lab for
Yes, sure. You Can do this if your aim as you stated in the question is to find a differential metabolite between the two groups.
Originally, you analysed your samples in both modes to get as much data as you can to select the top-ranked metabolites. Then after you know the top-ranked metabolites (e.g: by PLSDA VIP scores or other statistical tests), you will get more information about which mode yielded the most significant metabolites. This is like cleaning up your data that help you to proceed further and decide which mode works best for your kind of data.
Mixed data types can indeed be combined and co-analysed- it is possible to do pattern recognition on a variety of data in a single analysis if those data are scaled and normalised in the same way. The easiest is to analyse separately as noted above and just combine the lists-but it is tricky to compare the variance associated with the classification in this way because of the differential normalisation. However, how you do this optimally it is very dependent on the question you are asking and whether it is a list of metabolites/biomarkers or the relationship between biomarkers from different methods (including neg and pos ionisation) that you are looking for or whether you are interested in expressing graphically the final biology (which actually is the only thing that matters). One way to combine highly disparate types of data e.g. NMR plus MS is to do statistical heterospectroscopy - which works on the correlation matrix between data collected orthogonally on the same samples..also a homospectroscopic negative/positive MS ionisation map could be constructed to find the correlations between the species detected. Another totally different way to look at it is to do a metabonetworks analysis which is quite independent of the analytical technology because it only takes the validated biomarkers from each method. A couple of papers might help?
Yes you can, probably I am late here but the combo MS-DIAL and MS-CleanR might help you
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