EndoDB: a database of endothelial cell transcriptomics data

• Published in: Nucleic acids research Vol. 47; no. D1; pp. D736 - D744
• Main Authors: Khan, Shawez, Taverna, Federico, Rohlenova, Katerina, Treps, Lucas, Geldhof, Vincent, de Rooij, Laura, Sokol, Liliana, Pircher, Andreas, Conradi, Lena-Christin, Kalucka, Joanna, Schoonjans, Luc, Eelen, Guy, Dewerchin, Mieke, Karakach, Tobias, Li, Xuri, Goveia, Jermaine, Carmeliet, Peter
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 08.01.2019
• Subjects: Animals; Computational Biology; Database Issue; Databases, Genetic; Endothelial Cells - metabolism; Gene Expression Regulation - genetics; Humans; Principal Component Analysis; Transcriptome - genetics
• ISSN: 0305-1048; 1362-4962
• DOI: 10.1093/nar/gky997

Abstract 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.