For non-proteomics MS QC it would be nice to have ..

[mwalzer]

For starters, something like this:

 {
   "accession": "QC:4000257",
   "name": "Detected Compounds",
   "value": 57
}

[mwalzer]

We have this for starters:

[Term]
id: MS:4000102
name: number of detected quantification data points
def: "The number of data points detected for quantification purposes within the run. These data points may be for example XIC profiles, isotopic pattern areas, or reporter ions (see MS:1001805). The used type should be noted in the metadata or analysis methods section of the recording file for the respective run." [PSI:MS]
is_a: MS:4000003 ! single value
relationship: has_metric_category MS:4000009 ! ID free metric
relationship: has_metric_category MS:4000012 ! single run based metric
relationship: has_value_type xsd:int ! The allowed value-type for this CV term
relationship: has_units UO:0000189 ! count unit

[Term]
id: MS:4000103
name: number of identified quantification data points
def: "The number of identified data points for quantification purposes within the run after user defined acceptance criteria are applied.  These data points may be for example XIC profiles, isotopic pattern areas, or reporter ions (see MS:1001805). The used type should be noted in the metadata or analysis methods section of the recording file for the respective run. In case of multiple acceptance criteria (FDR) available in proteomics, PSM-level FDR should be used for better comparability." [PSI:MS]
is_a: MS:4000003 ! single value
relationship: has_metric_category MS:4000008 ! ID based metric
relationship: has_metric_category MS:4000012 ! single run based metric
relationship: has_value_type xsd:int ! The allowed value-type for this CV term
relationship: has_units UO:0000189 ! count unit

We'd need to document this better for someone in a field like say metabolomics to make the mental connection and get started.

[mwalzer]

But detected and identified components is just the start. What other 'usual suspects' are there?

[bittremieux]

We should take inspiration from established methods and tools in the field, such as:

• Guidelines and considerations for the use of system suitability and quality control samples in mass spectrometry assays applied in untargeted clinical metabolomic studies
• metabolomics Quality Assurance and quality Control Consortium (mQACC)
• msPurity
• Probably many more...