prideQC

prideQC computes quality-control metrics from raw mass-spectrometry data and uses that measured evidence to refine technical SDRF metadata.

It is designed around a simple separation of responsibilities:

1. Measure QC evidence from the data.
2. Summarize and report that evidence.
3. Refine metadata only when the study-level evidence supports it.

Documentation

• Documentation: https://prideqc.readthedocs.io/
• Source: https://github.com/PRIDE-Archive/prideQC
• PRIDE Archive: https://www.ebi.ac.uk/pride/

Until the hosted documentation is enabled, the same material is available under docs/ in this repository.

Highlights

prideQC can:

• analyze local mzML and supported raw/vendor inputs;
• compute per-file mass-spectrometry QC metrics;
• estimate precursor and fragment measurement precision;
• scout recurrent neutral mass shifts and mass-compatible modification candidates;
• write structured JSON, TSV, and mzQC-compatible outputs;
• aggregate results for interactive pmultiqc / MultiQC reporting;
• synthesize QC evidence across a study/cohort;
• propose conservative, auditable SDRF refinements;
• validate refined SDRFs with sdrf-pipelines.

Quick start

prideqc analyze sample1.mzML sample2.mzML \
  --output-dir results \
  --estimate-mass-error \
  --estimate-mass-shifts \
  --diagnostics

Refine an SDRF from existing QC results:

prideqc refine-sdrf-qc \
  --results-root results \
  --sdrf study.sdrf.tsv \
  --output-dir refinement

Validate an SDRF:

prideqc check-sdrf study.sdrf.tsv

Reporting

prideQC's mzQC-compatible outputs can be aggregated into interactive HTML reports with pmultiqc / MultiQC:

multiqc --module mzqc \
  --outdir report \
  results/

See the documentation for the complete QC, reporting, and SDRF-refinement workflow.

Local documentation build

uv venv .venv-docs --python 3.12
uv pip install --python .venv-docs/bin/python -r docs/requirements.txt
.venv-docs/bin/sphinx-build -W --keep-going -b html docs docs/_build/html

The six scientific SVG figures are checked into docs/_static/figures/; a normal Sphinx / Read the Docs build does not need pyOpenMS, matplotlib, or to regenerate the figures. For intentional figure regeneration, see the maintainer-only docs/figure_source/README.md.

License

See LICENSE, NOTICE, and licenses/.