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Publications

Citing quantms

If you use quantms in your research, please cite:

Dai C, Pfeuffer J, Wang H, Zheng P, Käll L, Sachsenberg T, Demichev V, Bai M, Kohlbacher O, Perez-Riverol Y. quantms: a cloud-based pipeline for quantitative proteomics enables the reanalysis of public proteomics data. Nature Methods. 2024;21:1603–1607. DOI: 10.1038/s41592-024-02343-1

Citing Tools Used by quantms

quantms integrates several tools. Please cite the relevant ones based on what your run used.

Search Engines

Comet

Eng JK, Jahan TA, Hoopmann MR. Comet: an open-source MS/MS sequence database search tool. Proteomics. 2013;13(1):22–24. DOI: 10.1002/pmic.201200439

MS-GF+

Kim S, Pevzner PA. MS-GF+ makes progress towards a universal database search tool for proteomics. Nature Communications. 2014;5:5277. DOI: 10.1038/ncomms6277

Sage

Lazear MR. Sage: An Open-Source Tool for Fast Proteomics Searching and Quantification at Scale. Journal of Proteome Research. 2023;22(11):3652–3659. DOI: 10.1021/acs.jproteome.3c00486

PSM Rescoring

MS2PIP

Declercq A, Bouwmeester R, Hirschler A, et al. MS2PIP: a tool for MS2 peak intensity prediction. Nucleic Acids Research. 2023;51(W1):W338–W342. DOI: 10.1093/nar/gkad335

DeepLC

Bouwmeester R, Gabriels R, Hulstaert N, et al. DeepLC can predict retention times for peptides that carry as-yet unseen modifications. Nature Methods. 2021;18:1363–1369. DOI: 10.1038/s41592-021-01301-5

Percolator

Käll L, Canterbury JD, Weston J, Noble WS, MacCoss MJ. Semi-supervised learning for peptide identification from shotgun proteomics datasets. Nature Methods. 2007;4:923–925. DOI: 10.1038/nmeth1113

MS2Rescore

Declercq A, Bouwmeester R, Chiva C, et al. MS2Rescore 3.0 Is a Modular, Flexible, and Scalable Framework to Boost Peptide Identifications at Any Scale. Molecular & Cellular Proteomics. 2024;23(4):100718. DOI: 10.1016/j.mcpro.2024.100718

Quantification and Post-processing

OpenMS

Pfeuffer J, Bielow C, Wein S, et al. OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data. Nature Methods. 2024;21:365–367. DOI: 10.1038/s41592-024-02197-7

MSstats

Choi M, Chang CY, Clough T, et al. MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments. Bioinformatics. 2014;30(17):2524–2526. DOI: 10.1093/bioinformatics/btu305

Quality Control

pmultiqc

Dai C, Füllgrabe A, Pfeuffer J, et al. A proteomics sample metadata representation for multiomics integration and big data analysis. Nature Communications. 2021;12:5854. DOI: 10.1038/s41467-021-26111-3

Metadata Standard

SDRF-Proteomics

Dai C, Füllgrabe A, Pfeuffer J, et al. A proteomics sample metadata representation for multiomics integration and big data analysis. Nature Communications. 2021;12:5854. DOI: 10.1038/s41467-021-26111-3

quantms.io data portal and format

Dai C, Pfeuffer J, Wang H, et al. quantms: a cloud-based pipeline for quantitative proteomics enables the reanalysis of public proteomics data. Nature Methods. 2024;21:1603–1607. DOI: 10.1038/s41592-024-02343-1

Community and Support

License

quantms is released under the MIT License.