ProteoFlux

ProteoFlux is an open-source Python framework for transparent, reproducible downstream analysis of quantitative proteomics data.

It operates on quantitative outputs generated by upstream search and quantification tools and provides a unified workflow for:

• Protein-centric proteomics
• Peptide-centric analyses
• Phosphoproteomics (with optional protein-level covariate adjustment)
• PELSA analyses

ProteoFlux emphasizes:

• Explicit data semantics
• Transparent preprocessing
• Deterministic statistical modeling
• Fully reproducible outputs

Overview

ProteoFlux takes a single YAML configuration file and produces:

• Harmonized and preprocessed quantification data
• Differential expression results using a limma-based empirical Bayes framework
• Principal component analysis (PCA), multidimensional scaling (MDS), and hierarchical clustering
• A structured multi-page PDF report
• Portable .h5ad files compatible with ProteoViewer
• Summary tables in Excel

Installation

Python ≥ 3.9 required.

Install from source (recommended)

git clone https://github.com/afanc/proteoflux.git
cd proteoflux
pip install -e .

This installs ProteoFlux in editable mode.

Quickstart (CLI)

List available configuration templates:

proteoflux templates

Create a template:

proteoflux init spectronaut-proteomics --path config.yaml

Edit the file and then run the full pipeline:

proteoflux run --config config.yaml

Output Files

The .h5ad files are compatible with ProteoViewer, an interactive visualization tool for ProteoFlux outputs.

Using ProteoFlux as a Python Library

ProteoFlux can also be used programmatically:

import yaml
from proteoflux.main import run_pipeline

config = yaml.safe_load(open("config.yaml")) #or use a dict
run_pipeline(config)

This allows:

• Integration into larger workflows
• Batch processing
• Use inside Jupyter notebooks
• Custom downstream analysis of AnnData objects

All behavior is controlled by the same YAML schema used by the CLI.

Configuration

All parameters are defined in a single YAML configuration file. We recommend starting with a template:

proteoflux templates
proteoflux init TEMPLATE_NAME

Full parameter reference:

See the configuration guide docs/CONFIGURATION.md.

Examples

Runnable, reduced example datasets and matching configs are provided under examples/:

• examples/searle_small/: small DIA proteomics example (Spectronaut export subset)
• examples/phospho_small/: phosphoproteomics example with an injected flow-through covariate run (Spectronaut export subsets)
• examples/pelsa_small/: small pelsa analysis example (Spectronaut export subsets)

Each example folder contains a README.md with a minimal command to run the pipeline (typically proteoflux run --config <config>.yaml) and the required input files (data + annotation, if applicable).

Paper

The manuscript source is provided as paper.md.

License

ProteoViewer is released under the MIT License. See the LICENSE file for details.

Citation

If you use ProteoFlux in your work, please cite:

ProteoFlux (latest version).
Zenodo. https://doi.org/10.5281/zenodo.18640998

A peer-reviewed publication is currently under submission.