DDA-PASEF · DIA-PASEF · RAW BAF · SERVICE BENCHMARKS
From inputs to protein and gene results
Analyze raw Bruker acquisitions or a quantification matrix. Get every condition comparison, quality control and matched service detection benchmarks. Every matrix is available as CSV and TSV.
1. Install once
Linux and Python 3.11 or newer:
pip install --upgrade fun_proteomics
fun_proteomics install --conda
fun_proteomics doctor
Download 12 ubiquitin-affinity samples: four conditions and three experimental replicates per condition. The archive includes quantities, sample assignments, checksums, original source files and attribution.
Discover the samples, review the four condition columns, confirm the replicate design, then save and run. This uses real quantified data and does not repeat a raw spectrum search.
Choose one launch method. --project is your output folder.setup --outdir is equivalent. Use a new project for a new analysis.
A) Interactive settings
fun_proteomics setup --project /data/my-study
Choose a matrix, raw-data folder or previous run, and review the output folder.
Click Discover samples, then drag sample cards into condition columns. Add or rename conditions; move exclusions to Unassigned. A sample table can prefill assignments.
Choose independent samples or paired matrix/BAF comparisons with donor IDs. Four conditions produce six condition pairs at each feature level.
Click Save configuration and check, then Run / continue analysis.
Open Results or Matrices · CSV & TSV in the same page.
Keep the terminal open during setup. Browse paths refer to the computer running the analysis.
For paired matrix/BAF data, replace --independent-samples with --subject-column donor. Add --service-matrix /data/provider.tsv for a matched service benchmark.
Check and run saved settings
fun_proteomics check --config /data/my-study/config/run.json
fun_proteomics run --config /data/my-study/config/run.json
Scan folders, drag acquisition cards into conditions, select a FASTA and check the project. This demo uses synthetic acquisition metadata and stops before spectrum searching.
Group technical injections under biological sample IDs, assign donors, choose an output folder, and review all six condition pairs. Synthetic placeholders are never searched.
The EV_PPC raw BAF analysis completed all 48 acquisitions, retained all four donors, and tested every condition pair at protein and gene levels. Review the execution evidence and matched-sample detection benchmarks across DDA, DDA+, DIA and BAF runs.