He, J. H. | Search bioRxiv

bioRxiv2026

SpatialArtifacts: a computational framework for tissue artifact detection in spatial transcriptomics data

Spatial transcriptomics data are frequently compromised by technical artifacts, such as dry patches, tissue lifting, and uneven reagent coverage, which manifests as regions with low UMI counts, in particular at tissue borders. It can often be challenging to identify these regions using existing quality control methods. Here, we present SpatialArtifacts, a framework that combines median absolute deviation (MAD)-based outlier detection with mathematical morphology operations to identify and classify spatially contiguous tissue artifacts. Focal operations including 3x3 fill, 5x5 outline, and star-pattern connectivity link low-quality spots while preserving true biological domains. We use a hierarchical classification system to distinguish edge versus interior artifacts and large versus small regions, enabling downstream removal or targeted manual review. We demonstrate the performance of our method in human hippocampus, dorsolateral prefrontal cortex, and colorectal cancer tissues using 10x Genomics Visium and VisiumHD platforms. Our SpatialArtifacts package is freely available on Bioconductor at https://bioconductor.org/packages/SpatialArtifacts and on PyPI at https://pypi.org/project/spatial-artifacts/.

bioinformatics↗

bioRxiv2025

Tissue transcriptomics of endomyocardial biopsies reveals widespread molecular perturbations independent of leukocyte-rich foci in human myocarditis

BackgroundMyocarditis is an inflammatory disease of the myocardium, classically defined and graded by histologic criteria that emphasize immune infiltrates and focal cardiomyocyte injury. The broader transcriptional landscape and intercellular signaling networks underlying human myocarditis, particularly among non-immune cells, remain poorly understood. MethodsWe performed integrated spatial transcriptomic profiling of 38 endomyocardial biopsy (EMBx) specimens using two complementary platforms: 10X Visium FFPE and GeoMx Digital Spatial Profiling (DSP). The cohort included cases of histologically confirmed myocarditis, borderline myocarditis, and controls. For 10X Visium, data was refined by excluding leukocyte-enriched spots and enriching for cardiomyocyte-specific regions based on canonical marker expression. For GeoMx, immunohistochemistry-guided segmentation enabled targeted transcriptomic analysis of disparate cardiac cellular compartments. Differential gene expression was analyzed independently for each platform and subsequently integrated. These results were further leveraged to infer molecular interaction networks and ligand-receptor relationships in myocarditis relative to controls. ResultsBoth platforms revealed widespread gene expression changes consistent with immune activation in myocarditis and borderline myocarditis, particularly within cardiomyocyte-enriched regions. These included upregulation of HLA-A, HLA-DQA1, B2M, and CD74 in myocarditis, consistent with activation of major histocompatibility complex (MHC) class I and II related pathways. Molecular interaction analysis identified STAT1 and ISG15 as likely central immune signaling nodes. Ligand-receptor inference highlighted HLA-A, HLA-E, and HLA-DQA1 as key receptor hubs interacting with immune ligands such as IFNG, CD8A, and several members of the (NK) killer-cell immunoglobulin-like receptor (KIR) family. ConclusionsOur findings demonstrate that human myocarditis is characterized by widespread transcriptional dysregulation beyond immune cell foci, including upregulation of genes typically associated with professional antigen-presenting cells in cardiomyocytes. These insights extend our current understanding of myocarditis pathophysiology and suggest new opportunities for its diagnosis and therapeutic targeting.

immunology↗