SpatialBench : Comparative cross-platform benchmarking of high-resolution spatial transcriptomics using matched mouse lymphoid tissue

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Authors: Ashleigh N. Solano, Raymond K. H. Yip, Changqing Wang, Daniela Amann-Zalcenstein, Pradeep Rajasekhar, Ishrat Zaman, Allan Motyer, Marek Cmero, Yang Xu, Yining Pan, Casey J. A. Anttila, Stephanie I. Studniberg
+13 more Peter F. Hickey, Layla Wang, Callum J. Sargeant, Ling Ling, Yunshun Chen, Ruvimbo D Mishi, Lisa J. Ioannidis, Kim L. Good‐Jacobson, Hamish W. King, Kelly L. Rogers, Diana S. Hansen, Bowden Rory, Matthew E. Ritchie
Cited by: 1
References: 69

Abstract

Spatial transcriptomics (ST) has rapidly expanded with the introduction of multiple high-resolution platforms, yet cross-platform benchmarking remains limited and largely focused on technical performance. Here we present SpatialBench , a matched multi-platform resource comprising Visium HD, Xenium and MERSCOPE data together with single-cell and single-nucleus references from a malaria-challenged wild-type and B cell-specific Tbx21 knockout mouse spleen model. In this system, loss of T-bet in B cells disrupts germinal center (GC) polarization and antibody maturation, providing a biologically grounded benchmark for technology comparison. We leveraged this system to systematically evaluate ST platform performance using technical and biological readouts. Across platforms, immune organization and Tbx21 -associated programs were consistently recovered, indicating robustness of major biological signals. Platforms instead differed in the level of biological resolution accessible. Visium HD enabled transcriptome-scale GC characterization and, together with Xenium, resolved dark and light zone organization, whereas GC zonation was not resolved in MERSCOPE, consistent with differences in transcript detection sensitivity. SpatialBench provides a biologically defined reference dataset for evaluation of ST technologies, method development, computational benchmarking, and studies of GC spatial organization in lymphoid tissue.

Fields of Study & Subjects

Single-cell and spatial transcriptomics Immune cells in cancer Cell Image Analysis Techniques

Publication details

Journal / source
bioRxiv (Cold Spring Harbor Laboratory)
Publisher
openRxiv
Publication date
1 May 2026
Document type
Preprint