Unveiling the links between peptide identification and differential analysis FDR controls by means of a practical introduction to knockoff filters

L Etourneau, N Varoquaux, T Burger - Statistical analysis of proteomic …, 2021 - Springer
Statistical analysis of proteomic data: Methods and tools, 2021Springer
In proteomic differential analysis, FDR control is often performed through a multiple test
correction (ie, 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 …
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.
Springer
以上显示的是最相近的搜索结果。 查看全部搜索结果