The error of the Metabolite Adduct Decharger adduct grouping workflow

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1

There is an error in AccurateMassSearch. I don’t know where happened problem about the node.
Read 45372 entries from mapping file!
Read 9 entries from adduct file ‘D:\LIPIDMAPS\Adducts\PositiveAdducts.tsv’.
Read 8 entries from adduct file ‘D:\LIPIDMAPS\Adducts\NegativeAdducts.tsv’.
Error: Unable to read file (‘D’ found. Please use only valid element identifiers or modify share/OpenMS/CHEMISTRY/Elements.xml! in: Unknown element ‘D3’)

2

Do you have Deuterium somewhere? Currently, it is not possible to specify specific isotopes.
If absolutely necessary you could approximate it with H3.

3

It shouldn’t exist Deuterium. Back to the question,should I change the input file(my data)
And I also want to ask why there are two metaboliteAdductDecharge node.In this time I use one.
Read 45372 entries from mapping file!
Read 6 entries from adduct file ‘D:\LIPIDMAPS\Adducts\PositiveAdducts.tsv’.
Read 7 entries from adduct file ‘D:\LIPIDMAPS\Adducts\NegativeAdducts.tsv’.
Error: Unable to read file (‘D’ found. Please use only valid element identifiers or modify share/OpenMS/CHEMISTRY/Elements.xml! in: Unknown element ‘D3’)

4

But “D3” means there must be some deuterium or some error somewhere in your input files.

There are two MetaboliteAdductDechargers because trying to find the optimal adduct clustering with ALL potential adducts takes even longer. So we look for the most common adducts first, then for some less common adducts.

5

Ok,I think maybe It is the veision of node ,because I delete the Node MetaboliteAdductDecharger when it is wrong .However, in another without the MetaboliteAdductDecharger the workflow is ok.
the data should be right.

6

I find the output data has one ，I input the positive and the negative pattern come from one sample. Is it right? if I have many sample, should I part them into group?

7

Usually you use the same adducts for all of your samples (unless you know for sure that you will have different ones). It automatically picks the ones applicable (i.e. only negative ones for negative mode and vice versa).

8

Yeah , your meaning is that I can put the positive and the negative pattern data, and the result is ok?

9

Yes, that is correct.

10

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