ParTIpy: A Scalable Framework for Archetypal Analysis and Pareto Task Inference

This repository accompanies the preprint “ParTIpy: A Scalable Framework for Archetypal Analysis and Pareto Task Inference”.

It contains the code to reproduce benchmarks of initialization and optimization strategies, as well as experiments evaluating coreset sizes and performance gains in Archetypal Analysis.

For additional examples and applications of Archetypal Analysis and Pareto Task Inference on single-cell and spatial omics data, please refer to the documentation.

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Installation

We recommend installing dependencies with mamba (or conda)

mamba env remove -n partipy -y
mamba env create -n partipy -f env.yaml

This will install all required packages, including ParTIpy

Download Data

Benchmark and example datasets are downloaded automatically when running the benchmark scripts (via functions defined in utils/data_utils.py).

Benchmarks

Initialization & Optimization Algorithms

mamba activate partipy

python -m code.benchmark_algorithms.ms_bench
python -m code.benchmark_algorithms.ms_xenium_bench
python -m code.benchmark_algorithms.lupus_bench

python -m code.benchmark_algorithms.bench_meta

Coresets

mamba activate partipy

python -m code.benchmark_coresets.ms_coreset
python -m code.benchmark_coresets.ms_xenium_coreset
python -m code.benchmark_coresets.lupus_coreset

python -m code.benchmark_coresets.coreset_meta

python -m code.benchmark_coresets.ms_coreset_v2
python -m code.benchmark_coresets.ms_xenium_coreset_v2
python -m code.benchmark_coresets.lupus_coreset_v2

python -m code.benchmark_coresets.coreset_meta_v2

Memory

mamba activate partipy

python -m code.benchmark_memory.k562_memory_bench
python -m code.benchmark_memory.hct116_memory_bench
python -m code.benchmark_memory.hek293t_memory_bench

python -m code.benchmark_memory.k562_memory_bench_only_pca
python -m code.benchmark_memory.hct116_memory_bench_only_pca
python -m code.benchmark_memory.hek293t_memory_bench_only_pca

python -m code.benchmark_memory.memory_meta

Examples

Simulated Data

mamba activate partipy

python -m code.benchmark_algorithms.simulated_data

Hepatocyte Example

mamba activate partipy

python -m code.examples.hepatocyte_example

Fibroblast Cross-Condition Analysis

mamba activate partipy

mamba list --name base | awk '{print $1}' | \
  grep -vE '^(#|'"$(paste -sd'|' keep.txt)"')$' \
  > remove.txt
python -m code.examples.fibroblast_cross_condition --quick

Additional Scripts

mamba activate partipy

python -m code.examples.overview_figure
python -m code.examples.delta_visualization

Citing ParTIpy

If you use ParTIpy in your work, please cite the following preprint:

@article{schaefer2025partipy,
  title   = {ParTIpy: A Scalable Framework for Archetypal Analysis and Pareto Task Inference},
  author  = {Schäfer, Philipp S. L. and Zimmermann, Leoni and Burmedi, Paul L. and Walfisch, Avia and Goldenberg, Noa and Yonassi, Shira and Shaer Tamar, Einat and Adler, Miri and Tanevski, Jovan and Ramirez Flores, Ricardo O. and Saez-Rodriguez, Julio},
  year    = {2025},
  journal = {bioRxiv},
  doi     = {10.1101/xxxxxx},
}