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Abstract
Quantitative proteomics has matured into an established tool and longitudinal proteomics experiments have begun to emerge. However, no effective, simple-to-use differential expression method for longitudinal proteomics data has been released. Typically, such data is noisy, contains missing values, and has only few time points and biological replicates. To address this need, we provide a comprehensive evaluation of several existing differential expression methods for high-throughput longitudinal omics data and introduce a Robust longitudinal Differential Expression (RolDE) approach. The methods are evaluated using over 3000 semi-simulated spike-in proteomics datasets and three large experimental datasets. In the comparisons, RolDE performs overall best; it is most tolerant to missing values, displays good reproducibility and is the top method in ranking the results in a biologically meaningful way. Furthermore, RolDE is suitable for different types of data with typically unknown patterns in longitudinal expression and can be applied by non-experienced users.
Longitudinal proteomics holds great promise for biomarker discovery, but the data interpretation has remained a challenge. Here, the authors evaluate several tools to detect longitudinal differential expression in proteomics data and introduce RolDE, a robust reproducibility optimization approach.
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1 University of Turku and Åbo Akademi University, Turku Bioscience Centre, Turku, Finland (GRID:grid.1374.1) (ISNI:0000 0001 2097 1371)
2 University of Maryland – Baltimore, Baltimore, USA (GRID:grid.411024.2) (ISNI:0000 0001 2175 4264)
3 US Army 20th Support Command CBRNE Analytical and Remediation Activity, Baltimore, USA (GRID:grid.505441.1)
4 University of Victoria, Victoria, Canada (GRID:grid.143640.4) (ISNI:0000 0004 1936 9465); International Centre for Cancer Vaccine Science, Gdansk, Poland (GRID:grid.143640.4)
5 University of Turku and Åbo Akademi University, Turku Bioscience Centre, Turku, Finland (GRID:grid.1374.1) (ISNI:0000 0001 2097 1371); University of Turku, Institute of Biomedicine, Turku, Finland (GRID:grid.1374.1) (ISNI:0000 0001 2097 1371)