Uses and misuses of the fudge factor in quantitative discovery proteomics
Open Access
- 7 June 2016
- journal article
- research article
- Published by Wiley in Proteomics
- Vol. 16 (14) , 1955-1960
Abstract
Selecting proteins with significant differential abundance is the cornerstone of many relative quantitative proteomics experiments. To do so, a trade‐off between p‐value thresholding and fold‐change thresholding can be performed because of a specific parameter, named fudge factor, and classically noted s0. We have observed that this fudge factor is routinely turned away from its original (and statistically valid) use, leading to important distortion in the distribution of p‐values, jeopardizing the protein differential analysis, as well as the subsequent biological conclusion. In this article, we provide a comprehensive viewpoint on this issue, as well as some guidelines to circumvent it.Keywords
Funding Information
- French National Agency for Research (ANR-10-INBS-08)
This publication has 19 references indexed in Scilit:
- In Vivo Phosphoproteomics Analysis Reveals the Cardiac Targets of β-Adrenergic Receptor SignalingScience Signaling, 2013
- Proteomics-based identification of low-abundance signaling and regulatory protein complexes in native plant tissuesNature Protocols, 2012
- Stoichiometry of chromatin-associated protein complexes revealed by label-free quantitative mass spectrometry-based proteomicsNucleic Acids Research, 2012
- Comparative Proteomic Analysis of Eleven Common Cell Lines Reveals Ubiquitous but Varying Expression of Most ProteinsMolecular & Cellular Proteomics, 2012
- Quantitative proteomics combined with BAC TransgeneOmics reveals in vivo protein interactionsJournal of Cell Biology, 2010
- Normalization and Statistical Analysis of Quantitative Proteomics Data Generated by Metabolic LabelingMolecular & Cellular Proteomics, 2009
- Testing significance relative to a fold-change threshold is a TREATBioinformatics, 2009
- An Investigation on Performance of Significance Analysis of Microarray (SAM) for the Comparisons of Several Treatments with one Control in the Presence of Small‐variance GenesBiometrical Journal, 2008
- Significance analysis of microarrays applied to the ionizing radiation responseProceedings of the National Academy of Sciences, 2001
- Analysis of protein patterns during differentiation using 2‐D electrophoresis and computer multidimensional classificationElectrophoresis, 1983