Univ. Grenoble Alpes, CEA, INSERM, BioSanté U1292, Grenoble, France.
Univ. Grenoble Alpes, CNRS, TIMC, Grenoble, France.
Methods Mol Biol. 2023;2426:1-24. doi: 10.1007/978-1-0716-1967-4_1.
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.
在蛋白质组学差异分析中，通常通过多重检验校正（即原始 p 值的调整）来进行 FDR 控制。在本方案中，我们应用了一种最近的替代方法，基于所谓的 knockoff 滤波器。它与经典的肽鉴定中用于 FDR 控制的靶标诱饵竞争过程在概念上具有有趣的相似性。为了为从业人员提供蛋白质组学中 FDR 控制的统一理解，我们将 knockoff 过程应用于真实和模拟的定量数据集。利用这些比较，我们提出了对 knockoff 过程进行适应性调整，以更好地适应定量蛋白质组学数据的特异性（主要是很少的样本）。我们将 knockoff 过程的性能与经典的 Benjamini-Hochberg 过程的性能进行了比较，从而为靶标诱饵竞争的优缺点提供了新的认识。
