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Annotate an unknown feature with Duaer
In Duaer, work an MS feature that no library identified: library match, mass candidates, reference spectra, and MASST, one Duaer Data call per step.
What metabolic dark matter is
In Duaer, metabolic dark matter is the MS features that no library identifies: an m/z or an MS/MS spectrum with no annotation.
Duaer chains single-purpose Duaer Data offerings instead of one large tool: one call per step, then decide the next step from the result.
Steps
- With a USI, fetch the peaks and precursor m/z with Spectrum by USI.
- Match the peaks with MassBank spectra. A score of 0.8 or more with a matching precursor is a likely identification; skip to the last step.
- Without a match, list PubChem candidates with Mass candidates from the precursor m/z, adduct, and ppm.
- For the top candidates, get reference spectra with MoNA spectra (or MassBank by InChIKey) and compare the major fragments.
- Run MASST to see which public datasets contain the spectrum. One seen across several studies is more likely a real metabolite.
- For an identified or putative compound, add pathways and reactions with RefMet, KEGG, or Rhea.
With only an m/z (MS1), skip the spectrum, library match, and MASST steps. A feature usually takes 3 to 8 calls.
How to report
- Result: the compound name and InChIKey, or unknown.
- Evidence per step: the call, the top hit, and its score, ppm error, or dataset count.
- Confidence: identified for a library match, putative for a candidate with shared fragments, mass only when only the mass fits.
Mass alone never identifies a structure: glucose, galactose, and fructose share a formula.
Skill
Give this skill to an agent to run the steps with Duaer Data.
---
name: duaer-metabolic-dark-matter
description: >-
Work an unannotated metabolomics feature (an m/z or MS/MS spectrum that no library identified)
step by step with Duaer Data. Each step is one Duaer Data call that uses 1 Duaer credit.
---
# Duaer: annotate an unknown feature (metabolic dark matter)
Metabolic dark matter is the MS features that no library identifies. This Duaer skill chains single-purpose Duaer Data calls.
Run one step, read its result, then decide the next step. Report what each call returned.
## Input
One of:
- A USI (`mzspec:...`) of a public spectrum.
- MS/MS peaks (`mz:intensity` pairs) with the precursor m/z, an adduct guess, and the ion mode.
- Only an m/z (MS1 feature) with an adduct guess. Skip steps 1, 2, and 5.
## Steps
1. **Get peaks.** For a USI, call https://skills.duaer.com/spectrum.md. Keep `peaks` and `precursorMz`.
2. **Library match.** Call https://skills.duaer.com/massbank.md with `peaks` and `ionMode`.
A `score` of 0.8 or more with a matching precursor is a likely identification. If you have one, go to step 6.
3. **Mass candidates.** Call https://skills.duaer.com/mass-candidates.md with the precursor m/z, the adduct, and `ppm` (5 for high-resolution data).
4. **Compare candidates.** For the top candidates, call https://skills.duaer.com/mona.md with each `inchikey`
(or https://skills.duaer.com/massbank.md with `inchikey`). Compare reference `peaks` and `precursorType` with yours.
Shared major fragments support a candidate. No shared fragments rules it out.
5. **Where it occurs.** Call https://skills.duaer.com/masst.md with the USI or the peaks.
`library=public` lists public datasets that contain the same spectrum. `library=gnpsLibrary` finds GNPS reference spectra.
A spectrum seen across several studies or sample types is more likely a real metabolite than noise.
6. **Context.** For an identified or putative compound, use https://skills.duaer.com/refmet.md for the standard name and class,
and https://skills.duaer.com/kegg.md or https://skills.duaer.com/rhea.md for pathways and reactions.
## Report
For each feature return:
- Input (USI, precursor m/z, adduct, ion mode).
- Result: the compound name and InChIKey, or `unknown`.
- Evidence per step: the call, the top hit, and its score, ppm error, or dataset count.
- Confidence: `identified` (library spectrum match), `putative` (candidate with shared fragments), `mass only`, or `unknown`.
- A next step, such as running an authentic standard.
## Rules
- Mass alone never identifies a compound. Isomers share a formula (glucose, galactose, fructose).
- Cite only returned results. Do not invent names, InChIKeys, scores, or datasets.
- One Duaer Data call per step. A feature usually takes 3 to 8 calls.
## Keys
Header: `Authorization: Bearer <Duaer key>`
Use an account key or a model API key.
Get a Duaer key: https://skills.duaer.com/keys.md
## Credits
Each successful Duaer Data call uses 1 credit, including a call that finds no match.
Empty input, a failed source, or no remaining credits uses 0.
Questions
How many credits does annotating one unknown feature use in Duaer?
Each successful Duaer Data call uses 1 credit. A feature usually takes 3 to 8 calls.
Does Duaer determine the structure of an unknown?
Not by itself. Duaer returns evidence (library matches, candidates, and where the spectrum occurs) with a confidence level; an authentic standard confirms the structure.
In this section
Fetch a spectrum by USI in Duaer
In Duaer, fetch the peaks of a public mass spectrum by its USI. One successful search uses 1 credit.
Get startedMatch spectra in MassBank with Duaer
In Duaer, match MS/MS peaks, an exact mass, or an InChIKey against MassBank. One successful search uses 1 credit.
Get startedList mass candidates in Duaer
In Duaer, list PubChem compounds that fit an observed m/z and adduct. One successful search uses 1 credit.
Get startedFind MoNA reference spectra with Duaer
In Duaer, find reference MS/MS spectra in MoNA by InChIKey or compound name. One successful search uses 1 credit.
Get startedSearch a spectrum with MASST in Duaer
In Duaer, find where an MS/MS spectrum appears in public metabolomics data with GNPS2 MASST. One successful search uses 1 credit.
Get startedSearch RefMet in Duaer
In Duaer, search metabolites in Metabolomics Workbench RefMet. One successful search uses 1 credit.