Datasets & Tools
Bioinformatics & Research Data
A central component of our research is bioinformatic analysis. We work with bulk RNA-seq, single-cell RNA-seq (scRNA-seq), and single-nuclei RNA-seq (snRNA-seq) data to study gene expression regulation, immune cell dynamics, and RNA-mediated mechanisms across cardiovascular diseases.
We created www.ircas.eu as an open-access platform hosting our scRNA-seq data from peripheral blood mononuclear cells (PBMCs) of patients with acute myocardial infarction with cardiogenic shock. The site includes an interactive, user-friendly analysis tool enabling researchers to investigate immune cell states and regulatory pathways in this critical clinical condition.
Many of our other datasets are also freely available for download via Gene Expression Omnibus (GEO), supporting reproducibility and open science initiatives:
Circulating immune cell signature analysis in HFpEF across species
This SuperSeries provides a multi-species transcriptomic resource to define circulating immune cell dysregulation in heart failure with preserved ejection fraction (HFpEF). It includes:
- scRNA-seq of PBMCs from a translational mouse HFpEF model
- Bulk RNA-seq of PBMCs from the same HFpEF mouse model
- Bulk RNA-seq of human PBMCs treated with IL-1β and the electrophilic fatty acid NO₂-OA
Together, these datasets identify a conserved HFpEF-associated immune signature across species and provide mechanistic insights into inflammatory pathways relevant to HFpEF pathophysiology.
Species:
Material: PBMCs
Sample#: 39
Novel Long Noncoding RNA HEAT4 Affects Monocyte Subtypes, Reducing Inflammation and Promoting Vascular Healing
This SuperSeries comprises a comprehensive multi-modal sequencing resource to characterize the function of the human-specific lncRNA HEAT4 in monocytes and circulating immune cells. It includes:
- scRNA-seq of PBMCs from patients and healthy controls
- scRNA-seq of monocytes with and without HEAT4 overexpression
- Bulk RNA-seq following HEAT4 overexpression and knockdown in primary human monocytes
- RIP-seq profiling S100A9-associated lncRNAs in human monocytes
- ChIP-seq of S100A9 in human monocytes with and without HEAT4 overexpression, combined with IL-10 stimulation, to dissect transcriptional regulation
Species:
Material: PBMCs/ monocytes
Sample#: 53
Rubella virus infection in endothelial cells reduces angiogenesis via interferon beta-induced CXCL10
This dataset contains bulk RNA-seq of human umbilical vein endothelial cells (HUVECs) infected with rubella virus. RuV induces a strong type I/III interferon response with marked CXCL10 upregulation, leading to impaired endothelial angiogenesis. To dissect the contribution of interferon signalling, endothelial cells were additionally treated with IFN-β, IFN-λ1, or both, followed by RNA-seq. The data highlight an IFN–CXCL10-driven pathway as a central mechanism of endothelial dysfunction during RuV infection and point to potential therapeutic targets relevant to congenital rubella syndrome.
Species:
Material: HUVECs
Sample#: 19
Leptin treatment has vasculo-protective effects in lipodystrophic mice
This dataset contains scRNA-seq profiling of human umbilical vein endothelial cells (HUVECs) to examine how leptin modulates endothelial-to-mesenchymal transition (EndMT). The dataset reveals that leptin counteracts EndMT-associated inflammatory activation, reduces mesenchymal gene expression, and preserves endothelial barrier integrity. These transcriptional changes align with in vivo findings showing that leptin reduces vascular inflammation, macrophage accumulation, and EndMT in lipodystrophic, atherosclerosis-prone mice—identifying leptin as a vasculo-protective regulator acting in part through suppression of GDF15.
Species:
Material: HUVECs
Sample#: 3
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Learn More About Our Research
Discover how our datasets support ongoing projects in RNA biology, immune–vascular interactions, and cardiometabolic disease.
Explore Related Publications
Many of the datasets on this page are connected to peer-reviewed studies from the Boeckel Lab. Browse our full list of publications to dive deeper into the findings behind the data.