References

Citing ProteoPy

If you use ProteoPy in your research, please cite:

[FTNS+26]

Fichtner ID, Temesvari-Nagy L, Sahm F, Gerstung M, and Bludau I. ProteoPy: an AnnData-based framework for integrated proteomics analysis. bioRxiv, 2026. Preprint. URL: https://www.biorxiv.org/content/10.64898/2026.03.31.715273v1, doi:10.64898/2026.03.31.715273.

@article{fichtner2026proteopy,
    title={{ProteoPy}: an {AnnData}-based framework for integrated proteomics analysis},
    author={Fichtner, Ian Dirk and Temesvari-Nagy, Levente and Sahm, Felix and Gerstung, Moritz and Bludau, Isabell},
    journal={bioRxiv},
    year={2026},
    doi={10.64898/2026.03.31.715273},
    url={https://www.biorxiv.org/content/10.64898/2026.03.31.715273v1},
    note={Preprint}
}

COPF algorithm

If you use the COPF proteoform inference functionality, please also cite:

[BFD+21]

Bludau I, Frank M, Dörig C, Cai Y, Heusel M, Rosenberger G, Picotti P, Collins BC, Röst H, and Aebersold R. Systematic detection of functional proteoform groups from bottom-up proteomic datasets. Nature Communications, 12:3810, 2021. URL: https://www.nature.com/articles/s41467-021-24030-x, doi:10.1038/s41467-021-24030-x.

@article{bludau2021systematic,
    title={Systematic detection of functional proteoform groups from bottom-up proteomic datasets},
    author={Bludau, Isabell and Frank, Max and D{\"o}rig, Christian and Cai, Yujia and Heusel, Moritz and Rosenberger, George and Picotti, Paola and Collins, Ben C. and R{\"o}st, Hannes and Aebersold, Ruedi},
    journal={Nature Communications},
    volume={12},
    pages={3810},
    year={2021},
    doi={10.1038/s41467-021-24030-x}
}

Related Publications

AnnData Ecosystem

[BKS22]

Bredikhin D, Kats I, and Stegle O. MUON: multimodal omics analysis framework. Genome Biology, 23(1):1–12, 2022. URL: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02577-8, doi:10.1186/s13059-021-02577-8.

[VRT+24]

Virshup I, Rybakov S, Theis FJ, Angerer P, and Wolf FA. Anndata: access and store annotated data matrices. Journal of Open Source Software, 9(101):4371, 2024. URL: https://joss.theoj.org/papers/10.21105/joss.04371, doi:10.21105/joss.04371.

[WAT18]

Wolf FA, Angerer P, and Theis FJ. SCANPY: large-scale single-cell gene expression data analysis. Genome Biology, 19(1):15, 2018. URL: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-017-1382-0, doi:10.1186/s13059-017-1382-0.

Data Processing Software

[CM08]

Cox J and Mann M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nature Biotechnology, 26(12):1367–1372, 2008. URL: https://www.nature.com/articles/nbt.1511, doi:10.1038/nbt.1511.

[DMV+20]

Demichev V, Messner CB, Vernardis SI, Lilley KS, and Ralser M. DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput. Nature Methods, 17(1):41–44, 2020. URL: https://www.nature.com/articles/s41592-019-0638-x, doi:10.1038/s41592-019-0638-x.

Datasets

[KXB+20]

Karayel Ö, Xu P, Bludau I, Velan Bhoopalan S, Yao Y, Ana Rita FC, Santos A, Schulman BA, Alpi AF, Weiss MJ, and Mann M. Integrative proteomics reveals principles of dynamic phosphosignaling networks in human erythropoiesis. Molecular Systems Biology, 16(12):MSB20209813, 2020. URL: https://doi.org/10.15252/msb.20209813, doi:10.15252/msb.20209813.

[WWW+18]

Williams EG, Wu Y, Wolski W, Kim JY, Lan J, Hasan M, Halter C, Jha P, Ryu D, Auwerx J, and Aebersold R. Quantifying and Localizing the Mitochondrial Proteome Across Five Tissues in A Mouse Population. Molecular & Cellular Proteomics, 17(9):1766–1777, 2018. URL: https://www.mcponline.org/article/S1535-9476(20)32056-9/abstract, doi:10.1074/mcp.RA118.000554.