Bioinformatics pipeline for processing single-cell data
(2024)
Mass spectrometry based single cell proteomics.
In Methods in molecular biology (MIMB)
2817.
p.221-239
- Author
- Arthur Declercq (UGent) , Nina Demeulemeester, Ralf Gabriels (UGent) , Robbin Bouwmeester (UGent) , Sven Degroeve (UGent) and Lennart Martens (UGent)
- Organization
- Project
- Abstract
- Single-cell proteomics can offer valuable insights into dynamic cellular interactions, but identifying proteins at this level is challenging due to their low abundance. In this chapter, we present a state-of-the-art bioinformatics pipeline for single-cell proteomics that combines the search engine Sage (via SearchGUI), identification rescoring with MS2Rescore, quantification through FlashLFQ, and differential expression analysis using MSqRob2. MS2Rescore leverages LC-MS/MS behavior predictors, such as MS2PIP and DeepLC, to recalibrate scores with Percolator or mokapot. Combining these tools into a unified pipeline, this approach improves the detection of low-abundance peptides, resulting in increased identifications while maintaining stringent FDR thresholds.
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01JCG4ZYGWV4H6E1TQNYH7T8FF
- MLA
- Declercq, Arthur, et al. “Bioinformatics Pipeline for Processing Single-Cell Data.” Mass Spectrometry Based Single Cell Proteomics, edited by Akos Vegvari et al., vol. 2817, Humana, 2024, pp. 221–39, doi:10.1007/978-1-0716-3934-4_15.
- APA
- Declercq, A., Demeulemeester, N., Gabriels, R., Bouwmeester, R., Degroeve, S., & Martens, L. (2024). Bioinformatics pipeline for processing single-cell data. In A. Vegvari, J. Teppo, & R. A. Zubarev (Eds.), Mass spectrometry based single cell proteomics (Vol. 2817, pp. 221–239). https://doi.org/10.1007/978-1-0716-3934-4_15
- Chicago author-date
- Declercq, Arthur, Nina Demeulemeester, Ralf Gabriels, Robbin Bouwmeester, Sven Degroeve, and Lennart Martens. 2024. “Bioinformatics Pipeline for Processing Single-Cell Data.” In Mass Spectrometry Based Single Cell Proteomics, edited by Akos Vegvari, Jaakko Teppo, and Roman A. Zubarev, 2817:221–39. New York: Humana. https://doi.org/10.1007/978-1-0716-3934-4_15.
- Chicago author-date (all authors)
- Declercq, Arthur, Nina Demeulemeester, Ralf Gabriels, Robbin Bouwmeester, Sven Degroeve, and Lennart Martens. 2024. “Bioinformatics Pipeline for Processing Single-Cell Data.” In Mass Spectrometry Based Single Cell Proteomics, ed by. Akos Vegvari, Jaakko Teppo, and Roman A. Zubarev, 2817:221–239. New York: Humana. doi:10.1007/978-1-0716-3934-4_15.
- Vancouver
- 1.Declercq A, Demeulemeester N, Gabriels R, Bouwmeester R, Degroeve S, Martens L. Bioinformatics pipeline for processing single-cell data. In: Vegvari A, Teppo J, Zubarev RA, editors. Mass spectrometry based single cell proteomics. New York: Humana; 2024. p. 221–39.
- IEEE
- [1]A. Declercq, N. Demeulemeester, R. Gabriels, R. Bouwmeester, S. Degroeve, and L. Martens, “Bioinformatics pipeline for processing single-cell data,” in Mass spectrometry based single cell proteomics, vol. 2817, A. Vegvari, J. Teppo, and R. A. Zubarev, Eds. New York: Humana, 2024, pp. 221–239.
@incollection{01JCG4ZYGWV4H6E1TQNYH7T8FF,
abstract = {{Single-cell proteomics can offer valuable insights into dynamic cellular interactions, but identifying proteins at this level is challenging due to their low abundance. In this chapter, we present a state-of-the-art bioinformatics pipeline for single-cell proteomics that combines the search engine Sage (via SearchGUI), identification rescoring with MS2Rescore, quantification through FlashLFQ, and differential expression analysis using MSqRob2. MS2Rescore leverages LC-MS/MS behavior predictors, such as MS2PIP and DeepLC, to recalibrate scores with Percolator or mokapot. Combining these tools into a unified pipeline, this approach improves the detection of low-abundance peptides, resulting in increased identifications while maintaining stringent FDR thresholds.}},
author = {{Declercq, Arthur and Demeulemeester, Nina and Gabriels, Ralf and Bouwmeester, Robbin and Degroeve, Sven and Martens, Lennart}},
booktitle = {{Mass spectrometry based single cell proteomics}},
editor = {{Vegvari, Akos and Teppo, Jaakko and Zubarev, Roman A.}},
isbn = {{9781071639337}},
issn = {{1064-3745}},
language = {{eng}},
pages = {{221--239}},
publisher = {{Humana}},
series = {{Methods in molecular biology (MIMB)}},
title = {{Bioinformatics pipeline for processing single-cell data}},
url = {{http://doi.org/10.1007/978-1-0716-3934-4_15}},
volume = {{2817}},
year = {{2024}},
}
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