1D and 2D annotation enrichment: a statistical method integrating quantitative proteomics with complementary high-throughput data

By Jüergen Cox, Matthias Mann. BMC Bioinformatics, 2012

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Quantitative proteomics now provides abundance ratios for thousands of proteins upon perturbations. These need to be functionally interpreted and correlated to other types of quantitative genome-wide data such as the corresponding transcriptome changes. We describe a new method, 2D annotation enrichment, which compares quantitative data from any two 'omics' types in the context of categorical annotation of the proteins or genes. Suitable genome-wide categories are membership of proteins in biochemical pathways, their annotation with gene ontology terms, sub-cellular localization, presence of protein domains or membership in protein complexes. 2D annotation enrichment detects annotation terms whose members show consistent behavior in one or both of the data dimensions. This consistent behavior can be a correlation between the two data types, such as simultaneous up- or down-regulation in both data dimensions, or a lack thereof, such as regulation in one dimension but no change in the other. For the statistical formulation of the test we introduce a two-dimensional generalization of the nonparametric two-sample test. The false discovery rate is stringently controlled by correcting for multiple hypothesis testing. We also describe one-dimensional annotation enrichment, which can be applied to single omics data. The 1D and 2D annotation enrichment algorithms are freely available as part of the Perseus software.

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/5de879452c4dcc5b9077c87f836cea3f24d7c3a5

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Citations in the corpus

Plasma Proteome Profiling to Assess Human Health and Disease. (2016, methodology): “To bioinformatically analyze the functional nature of the plasma proteome, we used the ‘‘1D annotation’’ algorithm in the MaxQuant software (Cox and Mann, 2008, 2012), to assign UniProtKB keywords to distinct abundance ranges.”
Ultradeep human phosphoproteome reveals a distinct regulatory nature of Tyr and Ser/Thr-based signaling. (2014, methodology): “Without stimulation there was very little difference between ordered and disordered sites as judged by 2D enrichment analysis (Cox and Mann, 2012), suggesting that protein phosphorylation tends to occur independent of structure in unstimulated cells.”
L-Arginine Modulates T Cell Metabolism and Enhances Survival and Anti-tumor Activity (2016, methodology): “…RNAs, see Table S6 This paper N/A Software and Algorithms MaxQuant Cox and Mann, 2008 http://www.coxdocs.org/doku.php? id=maxquant:start Perseus Cox and Mann, 2012 http://www.coxdocs.org/doku.php?id=perseus:start Progenesis-QI Version 2.0 Nonlinear Dynamics, Waters…”
The MaxQuant computational platform for mass spectrometry-based shotgun proteomics (2016, methodology): “Many sophisticated applications of Perseus have been published in the literature, including machine learning–based classification of tumor types 30 , multiomics comparisons 31 and time series analysis of circadian proteomics data 32 .”