1. qcML is writeable & may be readable
Disney 1940
Dave Tabb, Stellenbosch University
April 20, 2018
“We have met the enemy and he is us.” --Pogo

2. Two different vector looks: unlabeled vector
<qualityParameter ID="metric01" cvRef="PSI-QC- CV" accession="QC: " name="QuaMeter IDFree Metric- Distribution of peak widths for the wide XICs">
<content cvRef="PSI-QC-CV" accession="QC: " unitCvRef="UO-CV" unitAccession="UO: " value="5"> {'XIC-FWHM':[ , , , , ]} </content></qualityParameter>
n-way Tuple
Sec
Maybe we write just JSON at some future point.

3. Named vector
<qualityParameter ID="metric001" cvRef="QC" accession="QC:TODO" name="iMonDB Ambient Humidity">
<content cvRef="QC" accession="QC: " unitCvRef="UO-CV" unitAccession="UO: " value="5"> {'min':48.3,'Q1':48.9, 'Q2':49.3,'Q3':49.6,'max':51.3}
</content></qualityParameter>

4. New structure: matrix (up to three dimensions, one unit/type)
<qualityParameter ID="metric01" cvRef="PSI- QC-CV" accession="QC: " name="QuaMeter SWATH Metric- Distn of TIC log intensity ratios by SWATH" unitCvRef="UO-CV" unitAccession="UO: "> <content cvRef="PSI-QC-CV" accession="QC:XXXXXXX" value="3 10" dim1Labels="Q1 Q2 Q3">{ 'SWATH01':[0.07,0.20,0.29], 'SWATH02':[0.19,0.88,1.14], 'SWATH03':[0.23,0.30,0.39], … 'SWATH09':[0.12,0.64,0.82], 'SWATH10':[0.11,0.26,0.49] }</content></qualityParameter>
Need CV for data structure
Dim
labels

5. Why allow for 3D matrices?
I want to categorize all precursors for a RAW file by three categorical variables:
Precursor charge state
Tryptic status (fully, semi, unconstrained)
Which SWATH it appears in

6. New structure: data frame (each column its own unit)
<qualityParameter ID="metric01" cvRef="PSI-QC-CV" accession="QC: " name="What are the measurements for peptides targeted for depletion?"> <content cvRef="PSI-QC-CV" accession="QC:3000XXXX" value="5 4" unitCvRef="UO-CV" unitAccession="UO:XXXXXXX UO:XXXXXXX UO: UO: ">{ 'Label': ["Biognosis","ALBU","FIBR","FIBR","HbA"], 'Peptide': ["VLTNASR","GVSGAR","GILLEAK","YEVCNK","WGAAPR"], 'Intensity':[27636,3767,3575,33763,1663], 'RT': [2635,3752,1643,2974,2287] }</content></qualityParameter>
Need CV for data frame

7. Not yet ready: reporting quality analysis in qcML
We hope to appropriate sample hierarchy / data relationships, perhaps from QuantML.
We need to represent data transforms, such as principal components analysis.
Results for an individual file (such as declaring RAW an outlier) requires context.
Judgments may be recorded in qcML.

8. MIAPE-QC is not necessarily about the qcML format.
Decision: The Quality Control MIAPE educates users on describing quality process.
Sample Handling: what strategies did you use to control or monitor carbamylation, IAM artifacts, and digestion efficiency?
Repeatability: what methods did you use to test extent of technical replicate similarity?
MIAPE-QC is not necessarily about the qcML format.

9. Closing thoughts
The Quality Control Working Group is not here to tell you your experiment is bad.
We want to arm the proteomics and metabolomics community with processes to limit variability.
We produce formats and tools that empower experimentalists to evaluate the quality status of their workflows.