Citations and References

December 9, 2025 · View on GitHub

This document provides comprehensive citations for all algorithms implemented in the onsite package, including original manuscripts, related work, and implementation references.

Algorithm Citations

AScore Algorithm

Primary Citation

Beausoleil, S. A., Villén, J., Gerber, S. A., Rush, J., & Gygi, S. P. (2006). A probability-based approach for high-throughput protein phosphorylation analysis and site localization. Nature Biotechnology, 24(10), 1285-1292.

DOI: 10.1038/nbt1240

BibTeX:

@article{beausoleil2006probability,
  title={A probability-based approach for high-throughput protein phosphorylation analysis and site localization},
  author={Beausoleil, Sean A and Vill{\'e}n, Judit and Gerber, Scott A and Rush, John and Gygi, Steven P},
  journal={Nature Biotechnology},
  volume={24},
  number={10},
  pages={1285--1292},
  year={2006},
  publisher={Nature Publishing Group}
}
  • PhosphoRS: Taus, T., et al. (2011). Universal and confident phosphorylation site localization using phosphoRS. Journal of Proteome Research, 10(12), 5354-5362.
  • LuciPHOr: Fermin, D., et al. (2013). LuciPHOr: algorithm for phosphorylation site localization with false localization rate estimation using modified target-decoy approach. Molecular & Cellular Proteomics, 12(11), 3409-3419.

PhosphoRS Algorithm

Primary Citation

Taus, T., Köcher, T., Pichler, P., Paschke, C., Schmidt, A., Henrich, C., & Mechtler, K. (2011). Universal and confident phosphorylation site localization using phosphoRS. Journal of Proteome Research, 10(12), 5354-5362.

DOI: 10.1021/pr200611n

BibTeX:

@article{taus2011universal,
  title={Universal and confident phosphorylation site localization using phosphoRS},
  author={Taus, Thomas and K{\"o}cher, Thomas and Pichler, Peter and Paschke, Christian and Schmidt, Andreas and Henrich, Christian and Mechtler, Karl},
  journal={Journal of Proteome Research},
  volume={10},
  number={12},
  pages={5354--5362},
  year={2011},
  publisher={ACS Publications}
}
  • compomics-utilities: Barsnes, H., Vaudel, M., Colaert, N., Helsens, K., Sickmann, A., Berven, F. S., & Martens, L. (2011). compomics-utilities: an open-source Java library for computational proteomics. BMC Bioinformatics, 12, 70.
  • AScore: Beausoleil, S. A., et al. (2006). A probability-based approach for high-throughput protein phosphorylation analysis and site localization. Nature Biotechnology, 24(10), 1285-1292.

LucXor (LuciPHOr2) Algorithm

Primary Citations

LuciPHOr (2013): Fermin, D., Walmsley, S. J., Gingras, A. C., Choi, H., & Nesvizhskii, A. I. (2013). LuciPHOr: algorithm for phosphorylation site localization with false localization rate estimation using modified target-decoy approach. Molecular & Cellular Proteomics, 12(11), 3409-3419.

DOI: 10.1074/mcp.M113.028928

BibTeX:

@article{fermin2013luciphor,
  title={LuciPHOr: algorithm for phosphorylation site localization with false localization rate estimation using modified target-decoy approach},
  author={Fermin, Damian and Walmsley, Scott J and Gingras, Anne-Claude and Choi, Hyungwon and Nesvizhskii, Alexey I},
  journal={Molecular \& Cellular Proteomics},
  volume={12},
  number={11},
  pages={3409--3419},
  year={2013},
  doi={10.1074/mcp.M113.028928}
}

LuciPHOr2 (2015): Fermin, D., Avtonomov, D., Choi, H., & Nesvizhskii, A. I. (2015). LuciPHOr2: site localization of generic post-translational modifications from tandem mass spectrometry data. Bioinformatics, 31(7), 1141-1143.

DOI: 10.1093/bioinformatics/btu788

BibTeX:

@article{fermin2015luciphor2,
  title={LuciPHOr2: site localization of generic post-translational modifications from tandem mass spectrometry data},
  author={Fermin, Damian and Avtonomov, Dmitry and Choi, Hyungwon and Nesvizhskii, Alexey I},
  journal={Bioinformatics},
  volume={31},
  number={7},
  pages={1141--1143},
  year={2015},
  doi={10.1093/bioinformatics/btu788}
}

pAla (Phospho-Alanine Decoy Method) (2022): Ramsbottom, K. A., Prakash, A., Riverol, Y. P., Camacho, O. M., Martin, M. J., Vizcaíno, J. A., Deutsch, E. W., & Jones, A. R. (2022). Method for Independent Estimation of the False Localization Rate for Phosphoproteomics. Journal of Proteome Research, 21(7), 1603-1615.

DOI: 10.1021/acs.jproteome.1c00827

PMID: 35640880; PMCID: PMC9251759

BibTeX:

@article{ramsbottom2022pala,
  title={Method for Independent Estimation of the False Localization Rate for Phosphoproteomics},
  author={Ramsbottom, Kirsty A and Prakash, Ananth and Riverol, Yasset Perez and Camacho, Oscar M and Martin, Maria J and Vizca{\'i}no, Juan Antonio and Deutsch, Eric W and Jones, Andrew R},
  journal={Journal of Proteome Research},
  volume={21},
  number={7},
  pages={1603--1615},
  year={2022},
  doi={10.1021/acs.jproteome.1c00827},
  pmid={35640880},
  pmcid={PMC9251759}
}
  • Target-Decoy Approach: Elias, J. E., & Gygi, S. P. (2007). Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry. Nature Methods, 4(3), 207-214.
  • FLR Estimation: Käll, L., et al. (2008). Posterior error probabilities and false discovery rates: two sides of the same coin. Journal of Proteome Research, 7(1), 40-44.

Software and Framework Citations

PyOpenMS

Röst, H. L., Sachsenberg, T., Aiche, S., Bielow, C., Weisser, H., Aicheler, F., Andreotti, S., Ehrlich, H. C., Gutenbrunner, P., Kenar, E., Liang, X., Nahnsen, S., Nilse, L., Pfeuffer, J., Rosenberger, G., Rurik, M., Schmitt, U., Veit, J., Walzer, M., Wojnar, D., Wolski, W. E., Schilling, O., Choudhary, J. S., Malmström, L., Aebersold, R., Reinert, K., & Kohlbacher, O. (2016). OpenMS: a flexible open-source software platform for mass spectrometry data analysis. Nature Methods, 13(9), 741-748.

DOI: 10.1038/nmeth.3959

OpenMS

Kohlbacher, O., Reinert, K., Gröpl, C., Lange, E., Pfeifer, N., Schulz-Trieglaff, O., & Sturm, M. (2007). TOPP--the OpenMS proteomics pipeline. Bioinformatics, 23(2), e191-e197.

DOI: 10.1093/bioinformatics/btl299

compomics-utilities

Barsnes, H., Vaudel, M., Colaert, N., Helsens, K., Sickmann, A., Berven, F. S., & Martens, L. (2011). compomics-utilities: an open-source Java library for computational proteomics. BMC Bioinformatics, 12, 70.

DOI: 10.1186/1471-2105-12-70

NumPy

Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R., Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A., Del Río, J. F., Wiebe, M., Peterson, P., Gérard-Marchant, P., Sheppard, K., Reddy, T., Weckesser, W., Abbasi, H., Gohlke, C., & Oliphant, T. E. (2020). Array programming with NumPy. Nature, 585(7825), 357-362.

DOI: 10.1038/s41586-020-2649-2

SciPy

Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S. J., Brett, M., Wilson, J., Millman, K. J., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E., Carey, C. J., Polat, İ., Feng, Y., Moore, E. W., VanderPlas, J., Laxalde, D., Perktold, J., Cimrman, R., Henriksen, I., Quintero, E. A., Harris, C. R., Archibald, A. M., Ribeiro, A. H., Pedregosa, F., van Mulbregt, P., & SciPy 1.0 Contributors. (2020). SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods, 17(3), 261-272.

DOI: 10.1038/s41592-019-0686-2

Methodological References

Phosphorylation Site Localization

  • Statistical Methods: Savitski, M. M., et al. (2011). Confident phosphorylation site localization using the Mascot Delta Score. Molecular & Cellular Proteomics, 10(2), M110.003830.
  • Site-Determining Ions: Steen, H., et al. (2006). The ABC's (and XYZ's) of peptide sequencing. Nature Reviews Molecular Cell Biology, 7(9), 633-643.

False Discovery Rate

  • FDR Control: Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B (Methodological), 57(1), 289-300.
  • Target-Decoy: Elias, J. E., & Gygi, S. P. (2007). Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry. Nature Methods, 4(3), 207-214.

Mass Spectrometry

  • Tandem MS: Aebersold, R., & Mann, M. (2003). Mass spectrometry-based proteomics. Nature, 422(6928), 198-207.
  • Fragmentation: Steen, H., & Mann, M. (2004). The ABC's (and XYZ's) of peptide sequencing. Nature Reviews Molecular Cell Biology, 5(9), 699-711.

Implementation References

Python Implementation

  • Python: Van Rossum, G., & Drake, F. L. (2009). Python 3 Reference Manual. CreateSpace.
  • NumPy: Harris, C. R., et al. (2020). Array programming with NumPy. Nature, 585(7825), 357-362.
  • SciPy: Virtanen, P., et al. (2020). SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods, 17(3), 261-272.

Multi-threading

  • Threading: Python Software Foundation. (2021). Python threading documentation. https://docs.python.org/3/library/threading.html
  • Parallel Processing: Amdahl, G. M. (1967). Validity of the single processor approach to achieving large scale computing capabilities. AFIPS Conference Proceedings, 30, 483-485.

How to Cite onsite

If you use onsite in your research, please cite:

onsite Package

onsite: Mass spectrometry post-translational 
modification localization tool. https://github.com/bigbio/onsite

Algorithm-Specific Citations

For AScore

Beausoleil, S. A., et al. (2006). A probability-based approach for high-throughput 
protein phosphorylation analysis and site localization. Nature Biotechnology, 
24(10), 1285-1292.

For PhosphoRS

Taus, T., et al. (2011). Universal and confident phosphorylation site 
localization using phosphoRS. Journal of Proteome Research, 10(12), 5354-5362.

For LucXor (LuciPHOr2)

Fermin, D., Walmsley, S. J., Gingras, A. C., Choi, H., & Nesvizhskii, A. I. (2013). 
LuciPHOr: algorithm for phosphorylation site localization with false localization rate 
estimation using modified target-decoy approach. Molecular & Cellular Proteomics, 
12(11), 3409-3419.

Fermin, D., Avtonomov, D., Choi, H., & Nesvizhskii, A. I. (2015). LuciPHOr2: site 
localization of generic post-translational modifications from tandem mass spectrometry 
data. Bioinformatics, 31(7), 1141-1143.

Additional Resources

Online Documentation

Tutorials and Examples

Community and Support

License and Acknowledgments

This software is licensed under the MIT License. See the LICENSE file for details.

Acknowledgments

onsite builds upon the excellent work of the original algorithm developers and the OpenMS community. We thank all contributors and users for their feedback and support.

Contributing

We welcome contributions to onsite. Please see our Contributing Guidelines for more information.