quantmsdiann manuscript: analysis code and run provenance
Analysis scripts, run inputs and figure sources for the quantmsdiann paper.
quantmsdiann is the SDRF-driven Nextflow/DIA-NN workflow at
https://github.com/bigbio/quantmsdiann (v2.2.0 was used for this paper).
| Folder | Content |
|---|
sdrf/ | The SDRF used by every run, verbatim; per-run Nextflow parameters (params.json, launch.txt, diann_config.cfg); runs.tsv (index of all 38 runs); the FASTA databases (fasta/). Supplementary Table 1 with links: sdrf/README.md. |
scripts/rebuild.py | All main-text and Supplementary Note 4-6 figures and manuscript numbers, as named stages. |
scripts/review_*.py | Supplementary Figures S6-S8 and Tables S3-S5 (added in revision). |
scripts/build_*.py, stage_pride_submission.py, zenodo_upload.py | Table S6 and the PRIDE / Zenodo deposition of the results. |
analysis/figures/ | Figure sources (SVG) and the small derived tables they are drawn from. |
methods.md | The counting rule used for every identification number. |
REPRODUCIBILITY.md | Figure/table -> public source -> command. |
Data
Every number is computed from public data. Our reanalysis results (DIA-NN reports, matrices,
logs) are on the PRIDE FTP under
https://ftp.pride.ebi.ac.uk/pub/databases/pride/resources/proteomes/quantmsdiann-benchmarks/
(and quantms-collections/ for three cell-line cohorts), one folder per dataset and DIA-NN
version; they are also deposited as a PRIDE reanalysis dataset and on Zenodo (see the paper's
Data Availability). The PRIDE dataset is available at
https://www.ebi.ac.uk/pride/archive/projects/PXD085732. The original deposits we compare against are on PRIDE / MassIVE; the
accessions are listed in sdrf/README.md. Large inputs are never committed:
each stage downloads what it needs into data/ (git-ignored) on first use.
What is in PXD085732
The PRIDE dataset holds 88 files; raw files are not re-uploaded.
| PRIDE type | Files | Content |
|---|
| EXPERIMENTAL_DESIGN | 38 | The SDRF of every run, as used (<dataset>_<version>_<name>.sdrf.tsv). |
| SEARCH | 35 | One <dataset>_<version>.zip per run with a DIA-NN search: quant_tables/ (report, matrices, stats), pipeline_info/, sdrf/ configs, pmultiqc/, run_metadata.json, nextflow.log. |
| OTHER | 14 | 9 <PXD>.qpx.zip exports (PXD046357 and PXD049412 have one per DIA-NN version), and 5 PXD071075_v2_5_0_sweep_*cores.zip with only launch.txt and nextflow_trace.txt. |
| RAW | 1 | raw_files.raw.zip: raw_files.txt and raw_files.tsv, every raw file processed with its URL in the original deposit. |
There are more SDRFs (38) than search zips (35) because the two sets cover different runs:
- 33 runs have both an SDRF and a DIA-NN search zip.
- 5 SDRFs belong to the PXD071075 node-count sweep (10, 50, 100, 200 and 300 cores, Fig. 2a).
These runs measured wall-clock time only, so their zips keep the Nextflow traces and no DIA-NN
report (type OTHER). The five SDRFs are the same file, one per sweep run.
- 2 search zips are the standalone DIA-NN runs of the paired comparison
(
Paired-standalone-PXD049412, Paired-standalone-PXD070049, Supplementary Note 8). Plain
DIA-NN takes no SDRF; their quantmsdiann counterparts carry the SDRF.
runs.tsv, extra.config and Table S6 are not in the PRIDE dataset; they are in this repository
and its Zenodo record (https://doi.org/10.5281/zenodo.23322361).
Setup and use
conda env create -f environment.yml # pins numpy<2, bundles rsvg-convert
conda activate quantmsdiann
python -m scripts.rebuild --list # stages and what they produce
python -m scripts.rebuild --all # data -> figures -> numbers
python -m scripts.rebuild --only fig2_validation
pytest tests/
(pip alternative: pip install -r analysis/requirements.txt.)
Identification counts follow one rule (methods.md §1): global counts at
Lib.Q.Value / Lib.PG.Q.Value <= 0.01, per-run counts at Q.Value / PG.Q.Value <= 0.01,
decoys dropped, no other filter. plexDIA and phosphoproteomics runs show workflow support
(runtime) only; their identification counts are not benchmarked across DIA-NN versions.
