Benchmarking spatial transcriptomics technologies with the multi-sample SpatialBenchVisium dataset

Du, MRM; Wang, C; Law, CW; Amann-Zalcenstein, D; Anttila, CJA; Ling, L; Hickey, PF; Sargeant, CJ; Chen, Y; Ioannidis, LJ; Rajasekhar, P; Yip, RKH; Rogers, KL; Hansen, DS; Bowden, R; Ritchie, ME

Author(s): Du, MRM; Wang, C; Law, CW; Amann-Zalcenstein, D; Anttila, CJA; Ling, L; Hickey, PF; Sargeant, CJ; Chen, Y; Ioannidis, LJ; Rajasekhar, P; Yip, RKH; Rogers, KL; Hansen, DS; Bowden, R; Ritchie, ME;
Details: Publication Year 2025-03-28,Volume 26,Issue #1,Page 77
Journal Title: Genome Biology
Abstract: BACKGROUND: Spatial transcriptomics allows gene expression to be measured within complex tissue contexts. Among the array of spatial capture technologies available is 10x Genomics' Visium platform, a popular method which enables transcriptome-wide profiling of tissue sections. Visium offers a range of sample handling and library construction methods which introduces a need for benchmarking to compare data quality and assess how well the technology can recover expected tissue features and biological signatures. RESULTS: Here we present SpatialBenchVisium, a unique reference dataset generated from spleen tissue of mice responding to malaria infection spanning several tissue preparation protocols (both fresh frozen and FFPE, with either manual or CytAssist tissue placement). We note better quality control metrics in reference samples prepared using probe-based capture methods, particularly those processed with CytAssist, validating the improvement in data quality produced with the platform. Our analysis of replicate samples extends to explore spatially variable gene detection, the outcomes of clustering and cell deconvolution using matched single-cell RNA-sequencing data and publicly available reference data to identify cell types and tissue regions expected in the spleen. Multi-sample differential expression analysis recovered known gene signatures related to biological sex or gene knockout.
Publisher: BMC
Keywords: Animals; *Benchmarking; *Spleen/metabolism; Mice; *Gene Expression Profiling/methods; Transcriptome; Female; Male; Malaria; Single-Cell Analysis/methods; 10x Visium; Benchmarking; Differential expression; Multi-sample analysis; Spatial transcriptomics
Research Division(s): Genetics and Gene Regulation; Advanced Technology and Biology; Cancer Biology and Stem Cells
PubMed ID: 40156041
Publisher's Version: https://doi.org/10.1186/s13059-025-03543-4
Open Access at Publisher's Site: https://doi.org/10.1186/s13059-025-03543-4
Terms of Use/Rights Notice: Refer to copyright notice on published article.

Creation Date: 2025-04-08 03:00:56

Last Modified: 2025-04-08 03:12:40