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Topic: compare metabolites across experiments (Read 4504 times) previous topic - next topic

compare metabolites across experiments

I am hoping to open a broad discussion on the best way to analyze metabolites across experiments. In particular, I am thinking about such comparisons in the context of storing untargeted metabolomics data in a database. My thinking is as follows:

1. Unidentified compounds (i.e. compounds that are not in existing databases) may be present in multiple experiments. In this context, an 'experiment' might be samples collected in the lab or from a set of field sites.
2. The presence/absence of these unidentified compounds across experiments will determine which compounds will be most interesting to identify. For example, a compound at mass X is found in all samples of type A. The mass X is not found in any databases of known compounds, but the frequency that the compound is found means that it is one that I should try to identify.

However, there are some major caveats with this since you have to decide how to align features (both m/z values and retention times) across sample runs and potentially even instruments. This is a major issue. But if we acknowledge the caveats, what is the best way to align metabolites from different experiments in a manner that allows us to store unknown metabolites in a database?

Alternatively, is it better to populate the data base with the m/z values and retention times from each experiment, and then setup a search engine to look within a given error window for m/z values and retention times?

Krista