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Proteomics. 2016 Jan;16(1):29-32. doi: 10.1002/pmic.201500189.

Calibration plot for proteomics: A graphical tool to visually check the assumptions underlying FDR control in quantitative experiments.

Giai Gianetto Q1,2,3, Combes F1,2,3, Ramus C1,4,2,3, Bruley C1,2,3, Couté Y1,2,3, Burger T1,4,2,3.

Author information

1
Univ. Grenoble Alpes, iRTSV-BGE, Grenoble, France.
2
CEA, iRTSV-BGE, Grenoble, France.
3
INSERM, BGE, Grenoble, France.
4
CNRS, iRTSV-BGE, Grenoble, France.

Erratum in

Abstract

In MS-based quantitative proteomics, the FDR control (i.e. the limitation of the number of proteins that are wrongly claimed as differentially abundant between several conditions) is a major postanalysis step. It is classically achieved thanks to a specific statistical procedure that computes the adjusted p-values of the putative differentially abundant proteins. Unfortunately, such adjustment is conservative only if the p-values are well-calibrated; the false discovery control being spuriously underestimated otherwise. However, well-calibration is a property that can be violated in some practical cases. To overcome this limitation, we propose a graphical method to straightforwardly and visually assess the p-value well-calibration, as well as the R codes to embed it in any pipeline. All MS data have been deposited in the ProteomeXchange with identifier PXD002370 (http://proteomecentral.proteomexchange.org/dataset/PXD002370).

KEYWORDS:

False discovery rate; Relative quantification experiments; Statistical significance

PMID:
26572953
DOI:
10.1002/pmic.201500189
[Indexed for MEDLINE]

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