[t0mdavid-m]

Requested by Tom · project thread

Before: the only way to judge a search's quality was to scroll each run's PSM table one file at a time. There was no view of target/decoy separation, mass calibration, or run-to-run consistency.

After: a new page, Workflow Results › Identification QC, puts three plots over all runs on one page:

• Score distribution: target and decoy PSMs overlaid, using the Percolator score. If Percolator didn't run, it falls back to −log10 of Comet's E-value. A dashed line marks the lowest target score that passes the PSM FDR set on the Configure page.
• Precursor mass error: a histogram in ppm of the target PSMs that pass the FDR, with the median marked. 13C isotope picks of up to three peaks are corrected before binning.
• PSMs per file: target PSMs per run as horizontal bars.

This is the first item on the list for parity with the QC tab of Timo Sachsenberg's ProSE web app (timosachsenberg/prose-web).

How: src/common/qc_plots.py reads the existing percolator_results and psm_filter idXMLs into one flat table per run (top hit only). Pages cache it with st.cache_data, keyed on file mtimes. The plots are Plotly figures shown through show_fig(). OpenMS-Insight has no histogram or bar component, so Plotly is used here. The workflow itself is unchanged.

Validation:

• pytest test_gui.py tests/: 123 passed, including 4 new tests in tests/test_qc_plots.py that run on synthetic idXMLs.
• pylint --errors-only: no errors in the new files.
• The page was rendered in Chromium against a workspace of three synthetic runs (about 3,500 PSMs).

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Generated by Claude Code

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