Abstract
In proteomic differential analysis, FDR control is often performed through a multiple test correction (i.e., the adjustment of the original p-values). In this protocol, we apply a recent and alternative method, based on so-called knockoff filters. It shares interesting conceptual similarities with the target–decoy competition procedure, classically used in proteomics for FDR control at peptide identification. To provide practitioners with a unified understanding of FDR control in proteomics, we apply the knockoff procedure on real and simulated quantitative datasets. Leveraging these comparisons, we propose to adapt the knockoff procedure to better fit the specificities of quantitative proteomic data (mainly very few samples). Performances of knockoff procedure are compared with those of the classical Benjamini–Hochberg procedure, hereby shedding a new light on the strengths and weaknesses of target–decoy competition.
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Acknowledgements
This work was supported by grants from the French National Research Agency: ProFI project (ANR-10-INBS-08), GRAL project (ANR-10-LABX-49-01), DATA@UGA and SYMER projects (ANR-15-IDEX-02) and MIAI @ Grenoble Alpes (ANR-19-P3IA-0003).
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Etourneau, L., Varoquaux, N., Burger, T. (2023). Unveiling the Links Between Peptide Identification and Differential Analysis FDR Controls by Means of a Practical Introduction to Knockoff Filters. In: Burger, T. (eds) Statistical Analysis of Proteomic Data. Methods in Molecular Biology, vol 2426. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1967-4_1
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DOI: https://doi.org/10.1007/978-1-0716-1967-4_1
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