fun_proteomics

Analyze Bruker DDA-PASEF and DIA-PASEF data, or import a MaxQuant Excel workbook / protein quantification table. Get protein and gene matrices, all-versus-all comparisons, quality control, and detection benchmarks against a service provider. Every matrix is delivered as CSV and TSV.

pip install fun_proteomics
fun_proteomics setup --project /data/my-study

--project is your output folder. --outdir is an equivalent setup option. The browser previews the full destination before saving: PROJECT/results/final_results/matrices/ holds protein and gene CSV/TSV files.

Already installed? pip install --upgrade fun_proteomics updates the launcher. PyPI package · Watch drag-and-drop setup

Start here

Install

Linux and Python 3.11 or newer:

python3 -m venv proteomics-env
source proteomics-env/bin/activate
python -m pip install fun_proteomics
fun_proteomics system --path /data/my-study
fun_proteomics install --conda
fun_proteomics doctor

The Python package installs the launcher and reporting code. install --conda prepares the pinned analysis runtime and R packages in a user-writable cache; it does not use sudo. Registered DDA search archives remain separate. If you already have R and the analysis tools, see reuse an installation.

Set up your analysis

fun_proteomics setup --project /data/my-study

Keep the terminal open. Setup opens a local browser: choose your input, click Discover samples, and drag sample cards into condition columns, just as in OncoTracer. Add or rename conditions, move cards between them, or return them to Unassigned to exclude them. Each card also has a condition dropdown. Then click Save configuration and check and Run / continue analysis. Results and progress appear in the same page. Use the Browse buttons to select files on the computer running the analysis.

For terminal questions, including over SSH:

fun_proteomics setup --terminal --project /data/my-study --run

Both interfaces save my-study/config/run.json. Browser assignments are also exported as config/sample_assignments.csv and .tsv, including exclusions. To review first, omit --run in terminal setup. Then:

fun_proteomics check --config /data/my-study/config/run.json
fun_proteomics run --config /data/my-study/config/run.json

check validates inputs and explains the planned comparisons. run starts the saved analysis or continues it. Choose independent biological replicates or paired matrix comparisons with explicit donor IDs. Four conditions produce six comparisons at each feature level.

Find results and continue

Open my-study/START_HERE.html for results or my-study/MATRICES.html for CSV/TSV downloads. Detailed deliverables live in my-study/results/final_results/.

fun_proteomics --continue /data/my-study

Completed native results are verified and reused. Incomplete reports are rebuilt from verified inputs; raw workflows resume their saved Nextflow session. Existing runs from earlier releases also accept --continue /path/to/run. Integrity checks and recovery details.

Native Python and direct Nextflow remain supported. See advanced commands for raw JSON configurations, the advanced raw editor, phosphoproteomics, DDA counts, and specialist settings.

MIT licensed. Maintained by cfarkas. The setup/check/run experience follows OncoTracer.