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Calibration plot for proteomics: A graphical tool to visually check the assumptions underlying FDR control in quantitative experiments
Authors:Quentin Giai Gianetto  Florence Combes  Claire Ramus  Christophe Bruley  Yohann Couté  Thomas Burger
Affiliation: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
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
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