Bioinformatics Pipeline for Processing Single-Cell Data

Arthur Declercq; Nina Demeulemeester; Ralf Gabriels; Robbin Bouwmeester; Sven Degroeve; Lennart Martens

doi:10.1007/978-1-0716-3934-4_15

Bioinformatics Pipeline for Processing Single-Cell Data

Methods Mol Biol. 2024:2817:221-239. doi: 10.1007/978-1-0716-3934-4_15.

Authors

Arthur Declercq^{1

2}, Nina Demeulemeester^{1

2

3}, Ralf Gabriels^{1

2}, Robbin Bouwmeester^{1

2}, Sven Degroeve^{1

2}, Lennart Martens^{4

5}

Affiliations

¹ VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium.
² Department of Biomolecular Medicine, Ghent University, Ghent, Belgium.
³ StatOmics, Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.
⁴ VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium. [email protected].
⁵ Department of Biomolecular Medicine, Ghent University, Ghent, Belgium. [email protected].

PMID: 38907156
DOI: 10.1007/978-1-0716-3934-4_15

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.

Keywords: Bioinformatics; DeepLC; MS2PIP; MS2Rescore; Machine learning; Single-cell proteomics.

MeSH terms

Chromatography, Liquid / methods
Computational Biology* / methods
Humans
Proteome / analysis
Proteomics* / methods
Search Engine
Single-Cell Analysis* / methods
Software*
Tandem Mass Spectrometry* / methods

Substances

Proteome