I am using the Polyomics Integrated Metabolomics Pipeline (PiMP) for metabolite feature analysis. After annotating my data, I have encountered cases where multiple potential metabolites are suggested for one detected feature.
For example, one of my detected features has been annotated with several potential metabolites including Furfuryl acetate;L-Tyrosine;o-Tyrosine;Meta-Tyrosine;Ethyl 3-furoate;Ethyl furoate;4,6,7-Trihydroxy-1,2,3,4-tetrahydroisoquinoline;4-Hydroxy-4-(3-pyridyl)-butanoic acid;gamma-Hydroxy-3-pyridinebutanoate;L-Threo-3-Phenylserine;Ethyl maltol;Ethyl maltol;Beta-Tyrosine;3-Amino-3-(4-hydroxyphenyl)propanoate;N-Hydroxy-L-phenylalanine;D-Tyrosine;2,4,5-Trihydroxytoluene;Gentisyl alcohol;DL-Tyrosine;4-Hydroxymethylcatechol;2,4,6-Trihydroxytoluene;2,3,5-Trihydroxytoluene;L-threo-3-Phenylserine;L-Tyrosine. The detected m/z and RT values are 182.0813 and 490.61.
My questions are:
1) What criteria or best practices should I follow to select the most appropriate metabolite(s) from the multiple candidates?
2) Is it advisable to use all the metabolites listed for pathway analysis, or is it better to consider factors like biological relevance to focus on one?
3) What are the potential issues with including all listed metabolites?
4)Are there specific tools or methods for validating metabolite identities to ensure accurate pathway mapping?
I would greatly appreciate any advice or experiences you can share regarding handling multiple metabolite annotations and conducting pathway analysis accurately.
Thank you!
PS: my samples are from human plasma and the method used is LC-MS untargeted metabolomics.
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