With an exponential growth in applications identifying protein post-translational modifications via mass spectrometry, discovery and presentation of motifs surrounding those modification sites have become increasingly desirable. Despite a few tools being designed, there is still a scarcity of effective and polyfunctional software for such analysis and illustrations. In this study, a versatile and user-friendly web tool is developed, motifeR, for extracting and visualizing statistically significant motifs from large datasets. Particularly, several functions are also integrated for processing multi-modification sites enrichment. Public datasets are applied to test their usability, indicating that some concurrent modification sites may form motifs and that peptides with low location probability may be not identified randomly and can be included to support motif discovery. In addition, for human phosphoproteomics datasets, the characterization of differential kinase signaling networks can be estimated and modeled by combining kinase-substrate relations based on the NetworKIN database as an optional feature for users. The motifeR toolkit can be conveniently operated by any scientific community or individuals, even those without any bioinformatics background and is freely available at https://www.omicsolution.org/wukong/motifeR.
Keywords: identification; motifs; posttranslational modification; proteomics; visualization.
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