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nf-core/quantms: Citations

Pipeline

Chengxin Dai, Julianus Pfeuffer, Hong Wang et al. quantms: A cloud-based pipeline for proteomics reanalysis enables the quantification of 17521 proteins in 9,502 human samples., 01 June 2023, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-3002027/v1]

Pipeline research manuscripts

  • proteogenomics

    Umer HM, Audain E, Zhu Y, Pfeuffer J, Sachsenberg T, Lehtiö J, Branca RM, Perez-Riverol Y. Generation of ENSEMBL-based proteogenomics databases boosts the identification of non-canonical peptides. Bioinformatics. 2022 Feb 7;38(5):1470-1472. doi: 10.1093/bioinformatics/btab838. PMID: 34904638; PMCID: PMC8825679.

  • lfq dda benchmark

    Bai M, Deng J, Dai C, Pfeuffer J, Sachsenberg T, Perez-Riverol Y. LFQ-Based Peptide and Protein Intensity Differential Expression Analysis. J Proteome Res. 2023 Jun 2;22(6):2114-2123. doi: 10.1021/acs.jproteome.2c00812. Epub 2023 May 23. PMID: 37220883; PMCID: PMC10243145.

  • tissue absolute expression

    Wang H, Dai C, Pfeuffer J, Sachsenberg T, Sanchez A, Bai M, Perez-Riverol Y. Tissue-based absolute quantification using large-scale TMT and LFQ experiments. Proteomics. 2023 Jul 24:e2300188. doi: 10.1002/pmic.202300188. Epub ahead of print. PMID: 37488995.

nf-core

Ewels PA, Peltzer A, Fillinger S, Patel H, Alneberg J, Wilm A, Garcia MU, Di Tommaso P, Nahnsen S. The nf-core framework for community-curated bioinformatics pipelines. Nat Biotechnol. 2020 Mar;38(3):276-278. doi: 10.1038/s41587-020-0439-x. PubMed PMID: 32055031.

Nextflow

Di Tommaso P, Chatzou M, Floden EW, Barja PP, Palumbo E, Notredame C. Nextflow enables reproducible computational workflows. Nat Biotechnol. 2017 Apr 11;35(4):316-319. doi: 10.1038/nbt.3820. PubMed PMID: 28398311.

Pipeline tools

  • thermorawfileparser

    Hulstaert N, Shofstahl J, Sachsenberg T, Walzer M, Barsnes H, Martens L, Perez-Riverol Y. ThermoRawFileParser: Modular, Scalable, and Cross-Platform RAW File Conversion. J Proteome Res. 2020 Jan 3;19(1):537-542. doi: 10.1021/acs.jproteome.9b00328. Epub 2019 Dec 6. PMID: 31755270; PMCID: PMC7116465.

  • sdrf-pipelines

    Dai C, Füllgrabe A, Pfeuffer J, Solovyeva EM, Deng J, Moreno P, Kamatchinathan S, Kundu DJ, George N, Fexova S, Grüning B, Föll MC, Griss J, Vaudel M, Audain E, Locard-Paulet M, Turewicz M, Eisenacher M, Uszkoreit J, Van Den Bossche T, Schwämmle V, Webel H, Schulze S, Bouyssié D, Jayaram S, Duggineni VK, Samaras P, Wilhelm M, Choi M, Wang M, Kohlbacher O, Brazma A, Papatheodorou I, Bandeira N, Deutsch EW, Vizcaíno JA, Bai M, Sachsenberg T, Levitsky LI, Perez-Riverol Y. A proteomics sample metadata representation for multiomics integration and big data analysis. Nat Commun. 2021 Oct 6;12(1):5854. doi: 10.1038/s41467-021-26111-3. PMID: 34615866; PMCID: PMC8494749.

  • OpenMS

    Röst HL., Sachsenberg T., Aiche S., Bielow C., Weisser H., Aicheler F., Andreotti S., Ehrlich HC., 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 WE., Schilling O., Choudhary JS, 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. PubMed PMID: 27575624; PubMed Central PMCID: PMC5617107.

  • DIA-NN

    Demichev V, Messner CB, Vernardis SI, Lilley KS, Ralser M. DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput. Nat Methods. 2020 Jan;17(1):41-44. doi: 10.1038/s41592-019-0638-x. Epub 2019 Nov 25. PMID: 31768060; PMCID: PMC6949130.

  • MSstats

    Choi M., Chang CY., Clough T., Broudy D., Killeen T., MacLean B., Vitek O. (2014). MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments. Bioinformatics (Oxford, England), 30(17), 2524–2526. doi: 10.1093/bioinformatics/btu305. PubMed PMID: 24794931.

  • Comet

    Eng JK., Jahan TA., Hoopmann MR. (2013). Comet: an open-source MS/MS sequence database search tool. Proteomics, 13(1), 22–24. doi: 10.1002/pmic.201200439. PubMed PMID: 23148064

  • MS-GF+

    Kim S., Pevzner PA. (2014). MS-GF+ makes progress towards a universal database search tool for proteomics. Nature communications, 5, 5277. doi: 10.1038/ncomms6277. PubMed PMID: 25358478; PubMed Central PMCID: PMC5036525

  • Sage

    Lazear MR. Sage: An Open-Source Tool for Fast Proteomics Searching and Quantification at Scale. J Proteome Res. 2023 Oct 11. doi: 10.1021/acs.jproteome.3c00486. Epub ahead of print. PMID: 37819886.

  • Epifany

    Pfeuffer J, Sachsenberg T, Dijkstra TMH, Serang O, Reinert K, Kohlbacher O. EPIFANY: A Method for Efficient High-Confidence Protein Inference. J Proteome Res. 2020 Mar 6;19(3):1060-1072. doi: 10.1021/acs.jproteome.9b00566. Epub 2020 Feb 13. PMID: 31975601; PMCID: PMC7583457.

  • Triqler

    The M, Käll L. Integrated Identification and Quantification Error Probabilities for Shotgun Proteomics. Mol Cell Proteomics. 2019 Mar;18(3):561-570. doi: 10.1074/mcp.RA118.001018. Epub 2018 Nov 27. PMID: 30482846; PMCID: PMC6398204.

  • luciphor

    Fermin D, Walmsley SJ, Gingras AC, Choi H, Nesvizhskii AI. LuciPHOr: algorithm for phosphorylation site localization with false localization rate estimation using modified target-decoy approach. Mol Cell Proteomics. 2013 Nov;12(11):3409-19. doi: 10.1074/mcp.M113.028928. Epub 2013 Aug 5. PMID: 23918812; PMCID: PMC3820951.

  • MultiQC

    Ewels P, Magnusson M, Lundin S, Käller M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 2016 Oct 1;32(19):3047-8. doi: 10.1093/bioinformatics/btw354. Epub 2016 Jun 16. PubMed PMID: 27312411; PubMed Central PMCID: PMC5039924.

Software packaging/containerisation tools

  • Anaconda

    Anaconda Software Distribution. Computer software. Vers. 2-2.4.0. Anaconda, Nov. 2016. Web.

  • Bioconda

    Grüning B, Dale R, Sjödin A, Chapman BA, Rowe J, Tomkins-Tinch CH, Valieris R, Köster J; Bioconda Team. Bioconda: sustainable and comprehensive software distribution for the life sciences. Nat Methods. 2018 Jul;15(7):475-476. doi: 10.1038/s41592-018-0046-7. PubMed PMID: 29967506.

  • BioContainers

    da Veiga Leprevost F, Grüning B, Aflitos SA, Röst HL, Uszkoreit J, Barsnes H, Vaudel M, Moreno P, Gatto L, Weber J, Bai M, Jimenez RC, Sachsenberg T, Pfeuffer J, Alvarez RV, Griss J, Nesvizhskii AI, Perez-Riverol Y. BioContainers: an open-source and community-driven framework for software standardization. Bioinformatics. 2017 Aug 15;33(16):2580-2582. doi: 10.1093/bioinformatics/btx192. PubMed PMID: 28379341; PubMed Central PMCID: PMC5870671.

  • Docker

    Merkel, D. (2014). Docker: lightweight linux containers for consistent development and deployment. Linux Journal, 2014(239), 2. doi: 10.5555/2600239.2600241.

  • Singularity

    Kurtzer GM, Sochat V, Bauer MW. Singularity: Scientific containers for mobility of compute. PLoS One. 2017 May 11;12(5):e0177459. doi: 10.1371/journal.pone.0177459. eCollection 2017. PubMed PMID: 28494014; PubMed Central PMCID: PMC5426675.