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bioRxiv · 10.1101/2021.04.22.440981

Glycowork: A Python package for glycan data science and machine learning

Thomes, L.·Burkholz, R.·Bojar, D.
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Abstract

As a biological sequence, glycans occur in every domain of life and comprise monosaccharides that are chained together to form oligo- or polysaccharides. While glycans are crucial for most biological processes, existing analysis modalities make it difficult for researchers with limited computational background to include information from these diverse and nonlinear sequences into standard workflows. Here, we present glycowork, an open-source Python package that was designed for the processing and analysis of glycan data by end users, with a strong focus on glycan-related data science and machine learning. Glycowork includes numerous functions to, for instance, automatically annotate glycan motifs and analyze their distributions via heatmaps and statistical enrichment. We also provide visualization methods, routines to interact with stored databases, trained machine learning models, and learned glycan representations. We envision that glycowork can extract further insights from any glycan dataset and demonstrate this with several workflows that analyze glycan motifs in various biological contexts. Glycowork can be freely accessed at https://github.com/BojarLab/glycowork/.

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Thomes, L., Burkholz, R., Bojar, D.. 2021-04-22. Glycowork: A Python package for glycan data science and machine learning. https://doi.org/10.1101/2021.04.22.440981

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