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PreprintCC BY-NCbioRxiv

SENgEAR: an interactive visualization platform for comparative analysis of senescence signatures and cellular communication

  • S. Nagaraj
  • R. S. Adkins
  • A. N. Rindone
  • A. Das
  • D. Lesperance
  • J. Orvis
  • K. Krishnan
  • B. D. Cosgrove
  • N. Basisty
  • D. J. Baker
  • O. R. White
  • A. A. Mahurkar
2 more authors
  • J. H. Elisseeff
  • E. J. Fertig1
  1. 1Institute for Genome Sciences; Department of Epidemiology; Department of Medicine; Greenebaum Comprehensive Cancer Center; University of Maryland School of Medi
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Abstract

Single-cell and spatial transcriptomic datasets provide tremendous potential to identify the cellular states and communication networks associated with senescence. Annotating senescent cells in these datasets is hindered by the lack of universal markers for senescent cells and their context-dependent variability. To overcome this, several groups have developed gene signatures to annotate cells with distinct senotypes. However, comparing these signatures and their biological contexts to determine the specificity of senescence signatures remains complicated by the separate data platforms for signatures and datasets. We present SENgEAR, a no-code web platform for senescent cell annotation, visualization of cell-cell communication networks, and comparison of senescence signatures across studies, tissues, species, and data modalities. SENgEAR provides a unified framework to explore contextual signature specificity, cellular communication pathways, and senotype heterogeneity. We demonstrate the use of SENgEAR for applications spanning aging, fibrosis, and wound healing and its ability to interrelate these states.

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Cite

BibTeXRIS
BibTeX
@misc{nagaraj2026sengear,
  title = {{SENgEAR: an interactive visualization platform for comparative analysis of senescence signatures and cellular communication}},
  author = {S. Nagaraj and R. S. Adkins and A. N. Rindone and A. Das and D. Lesperance and J. Orvis and K. Krishnan and B. D. Cosgrove and N. Basisty and D. J. Baker and O. R. White and A. A. Mahurkar and J. H. Elisseeff and E. J. Fertig},
  howpublished = {bioRxiv},
  year = {2026},
  month = oct,
  doi = {10.64898/2026.10.31.763339},
  url = {https://www.biorxiv.org/content/10.64898/2026.10.31.763339v1},
  note = {CC BY-NC},
}
RIS
TY  - UNPB
TI  - SENgEAR: an interactive visualization platform for comparative analysis of senescence signatures and cellular communication
AU  - S. Nagaraj
AU  - R. S. Adkins
AU  - A. N. Rindone
AU  - A. Das
AU  - D. Lesperance
AU  - J. Orvis
AU  - K. Krishnan
AU  - B. D. Cosgrove
AU  - N. Basisty
AU  - D. J. Baker
AU  - O. R. White
AU  - A. A. Mahurkar
AU  - J. H. Elisseeff
AU  - E. J. Fertig
PY  - 2026
DA  - 2026/10/31
PB  - bioRxiv
DO  - 10.64898/2026.10.31.763339
UR  - https://www.biorxiv.org/content/10.64898/2026.10.31.763339v1
AB  - Single-cell and spatial transcriptomic datasets provide tremendous potential to identify the cellular states and communication networks associated with senescence. Annotating senescent cells in these datasets is hindered by the lack of universal markers for senescent cells and their context-dependent variability. To overcome this, several groups have developed gene signatures to annotate cells with distinct senotypes. However, comparing these signatures and their biological contexts to determine the specificity of senescence signatures remains complicated by the separate data platforms for signatures and datasets. We present SENgEAR, a no-code web platform for senescent cell annotation, visualization of cell-cell communication networks, and comparison of senescence signatures across studies, tissues, species, and data modalities. SENgEAR provides a unified framework to explore contextual signature specificity, cellular communication pathways, and senotype heterogeneity. We demonstrate the use of SENgEAR for applications spanning aging, fibrosis, and wound healing and its ability to interrelate these states.
ER  -