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

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.

Authors

Institutions

Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-11-02
DOI
https://doi.org/10.64898/2026.10.31.763339
Primary Topic
Single-cell and spatial transcriptomics
Type
preprint

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

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

Anup Mahurkar, Sushma Nagaraj, Ricky S. Adkins, Jennifer H. Elisseeff et al.
4 links
bioRxiv (Cold Spring Harbor Laboratory)
Single-cell and spatial transcriptomics
preprint

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

Anup Mahurkar, Sushma Nagaraj, Ricky S. Adkins, Jennifer H. Elisseeff, Joshua Orvis, Benjamin D. Cosgrove, Elana Judith Fertig, Nathan Basisty, Daniel Lesperance, Arun Das, Owen R. White, Alexandra N. Rindone, Kavita Krishnan, Darren J. Baker
preprint en

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.

bioRxiv (Cold Spring Harbor Laboratory)
University of Maryland, Baltimore (US), Mayo Clinic (US), Johns Hopkins University (US), Cornell University (US), National Institute on Aging (US), University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center (US)
University of Maryland, Baltimore
Single-cell and spatial transcriptomics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon