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The amount of biological data, generated with (single cell) omics technologies, is rapidly increasing, thereby exacerbating bottlenecks in the data analysis and interpretation of omics experiments. Data mining platforms that facilitate non-bioinformatician experimental scientists to analyze a wide range of experimental designs and data types can alleviate such bottlenecks, aiding in the exploration of (newly generated or publicly available) omics datasets. Here, we present BIOMEX, a browser-based software, designed to facilitate the Biological Interpretation Of Multi-omics EXperiments by bench scientists. BIOMEX integrates state-of-the-art statistical tools and field-tested algorithms into a flexible but well-defined workflow that accommodates metabolomics, transcriptomics, proteomics, mass cytometry and single cell data from different platforms and organisms. The BIOMEX workflow is accompanied by a manual and video tutorials that provide the necessary background to navigate the interface and get acquainted with the employed methods. BIOMEX guides the user through omics-tailored analyses, such as data pretreatment and normalization, dimensionality reduction, differential and enrichment analysis, pathway mapping, clustering, marker analysis, trajectory inference, meta-analysis and others. BIOMEX is fully interactive, allowing users to easily change parameters and generate customized plots exportable as high-quality publication-ready figures. BIOMEX is open source and freely available at https://www.vibcancer.be/software-tools/biomex. ispartof: NUCLEIC ACIDS RESEARCH vol:48 issue:W1 pages:W385-W394 ispartof: location:England status: published

Endothelial cells (ECs) line blood vessels, regulate homeostatic processes (blood flow, immune cell trafficking), but are also involved in many prevalent diseases. The increasing use of high-throughput technologies such as gene expression microarrays and (single cell) RNA sequencing generated a wealth of data on the molecular basis of EC (dys-)function. Extracting biological insight from these datasets is challenging for scientists who are not proficient in bioinformatics. To facilitate the re-use of publicly available EC transcriptomics data, we developed the endothelial database EndoDB, a web-accessible collection of expert curated, quality assured and pre-analyzed data collected from 360 datasets comprising a total of 4741 bulk and 5847 single cell endothelial transcriptomes from six different organisms. Unlike other added-value databases, EndoDB allows to easily retrieve and explore data of specific studies, determine under which conditions genes and pathways of interest are deregulated and assess reprogramming of metabolism via principal component analysis, differential gene expression analysis, gene set enrichment analysis, heatmaps and metabolic and transcription factor analysis, while single cell data are visualized as gene expression color-coded t-SNE plots. Plots and tables in EndoDB are customizable, downloadable and interactive. EndoDB is freely available at https://vibcancer.be/software-tools/endodb, and will be updated to include new studies. ispartof: NUCLEIC ACIDS RESEARCH vol:47 issue:D1 pages:D736-D744 ispartof: location:England status: published