spatial domain detection

spSheaf: sheaf-theoretic spatial domain inference from raw molecules without cell segmentation

spSheaf infers spatial domains from raw molecular data without cell segmentation, outperforming existing methods on benchmark datasets.

Statistical significance testing for spatial domain detection in spatial transcriptomics

SigDoTS is a statistical framework for spatial domain detection in spatial transcriptomics that controls for post-selection bias and improves domain recovery.

Spatial proteomics on repurposed sequencers reveals early astrocytic remodeling in an ALS mouse model

The paper develops a spatial proteomics workflow to study early astrocytic remodeling in an ALS mouse model, finding that motor neurons are surrounded by GFAP-high environments earlier than previously observed.

THiRST: Computer Vision Empowered Three-dimensional High-Resolution Spatial Transcriptomics Analytics

THiRST reconstructs 3D spatial transcriptomic data from serial 2D sections, improving cross-section consistency and enabling 3D gene expression analysis.

MorphoANOVA: Dissecting Histology-Gene Expression Relationships in Spatial Transcriptomics

MorphoANOVA systematically analyzes spatial gene-expression patterns in relation to tissue morphology, identifying genes with location-specific associations and spatial expression beyond morphology.

Three-dimensional mapping of human lung fibrosis identifies spatial coupling between tissue microarchitecture and maladaptive repair states

This study maps human lung fibrosis in 3D, showing how structural changes in tissue microarchitecture drive maladaptive repair states and disease progression.

Homeostatic fibroblast niche collapse in clinically uninvolved skin marks a pre-fibrotic stage of systemic sclerosis

The paper identifies a pre-fibrotic stage in scleroderma by analyzing spatial transcriptomic changes in clinically uninvolved skin, showing early loss of fibroblast niches and vascular reprogramming.

MorphoProt: RNA-Conditioned Integration of Multiscale Histology for Spatial Protein Inference

MorphoProt predicts spatial protein abundance using RNA expression, multiscale histology, and tissue neighborhoods, outperforming baselines in human and mouse tissues.

Single-probe, high-yield spatial mapping of diverse short RNA motifs

The paper introduces SMOOTHY-FISH, a method to visualize short RNA motifs at single-molecule resolution, revealing new spatial RNA biology insights in single cells and mouse brain tissues.

Generalizable virtual staining from histopathology to spatial proteomics across biological scales

This study introduces QUEST, a model that uses H&E histology to predict spatial protein expression, enabling virtual staining and analysis across biological scales.

Spatial transcriptomics of pediatric tuberculosis lymph nodes reveals a conserved hypoxia_SPP1 niche

This study uses spatial transcriptomics to identify a hypoxia-associated SPP1-enriched microenvironment in pediatric TB granulomas that may contribute to incomplete bacterial clearance.

WhaleSonic: Recordings of cetacean vocal behaviour with hydrophone arrays in Northern Norway

WhaleSonic provides a raw acoustic dataset of cetacean vocalizations in Northern Norway, supporting multichannel algorithms for source separation and communication analysis.

TileScope quantifies spatial gene expression relationships beyond colocalization

TileScope quantifies spatial gene expression relationships beyond simple colocalization, distinguishing regional enrichment from internal covariation in glioblastoma and other tissues.

TSNR: Protein-Specific Signals with Broad Molecular Context for Spatial Protein Prediction

The paper introduces TSNR, a method for spatial protein prediction that uses protein-specific signals and broad molecular context, achieving high correlation on a benchmark.

Quantifying subcellular organization from localization to co-occurrence with InSpace

InSpace quantifies subcellular organization by preserving localization and molecular co-occurrence, revealing spatial programs in B and plasma cells across cancers.

Kontext: Kernel-based method bridging spatial domain identification and cell-cell communication

Kontext identifies spatial domains and cell-cell communication by integrating ligand-receptor interactions, outperforming existing methods in spatial transcriptomics.

PatHoST: weakly supervised reconstruction of pathogen spatial distributions from host transcriptomes

PatHoST reconstructs pathogen spatial distributions from host transcriptomes using weakly supervised learning, showing improved detection in both experimental and human SARS-CoV-2 data.

Evolution of immune infiltration and immune triad formation across early melanoma progression

The paper investigates immune infiltration and triad formation in early melanoma progression using spatial transcriptomics, finding increased immune engagement in Stage I lesions compared to Stage 0.

smoothclust: Spatial smoothing and boundary-density summaries for spatial transcriptomics

smoothclust provides a framework for spatial domain analysis in spatial transcriptomics, including a clustering workflow and a boundary density metric to summarize tissue architecture.

Decoder-FFPE-seq enables sensitive, genome-wide spatial transcriptomics of archival tissues at single-cell resolution

Decoder-FFPE-seq improves sensitivity and resolution for spatial transcriptomics in FFPE tissues, enabling analysis of rare genes and tumor microenvironments.

Molecule-resolved inference reveals the spatial organization of transcriptional programs

The paper introduces FICTURE2, a statistical model that infers transcriptional programs from individual RNA molecules in spatial transcriptomics data, revealing spatial organization and cellular identity without segmentation.

Spatial Landscape of Pregnancy-Associated Triple Negative Breast Cancer and Mammary Gland Involution

This study compares transcriptional differences between pre- and post-involution PA-TNBC tissues using spatial transcriptomics, identifying distinct inflammatory and chromatin remodeling patterns in post-involution tumors.

Spatialsnake: a flexible workflow for spatial transcriptomics analysis across platforms

Spatialsnake provides a flexible workflow for spatial transcriptomics analysis across multiple platforms, enabling analysis of selected populations and tissue regions with adjustable parameters.

Gene context shapes spatial organization and transcriptional heterogeneity of extrachromosomal DNA in cancer cells

This study investigates how gene context influences the spatial organization and transcriptional behavior of extrachromosomal DNA in cancer cells using a new imaging method called FLAGx.

Multi-scale spatial transcriptomic atlas of the whole mouse spinal cord

The paper creates a spatial transcriptomic atlas of the whole mouse spinal cord, revealing multi-scale cellular organization and gene-expression patterns across different regions.

Metabolic niches: MALDI imaging reveals lipidomic heterogeneity in the human heart

This paper uses MALDI-MSI to create the first spatially resolved lipidomic atlas of the human heart, identifying region-specific lipid differences.

Quantitative assessment of mesoscale cellular order and organization in the mouse hippocampus

The paper quantifies mesoscale cellular organization in the mouse hippocampus using a new software tool, revealing cell-type-specific nuclear shape variations and positionally ordered but orientationally disordered dense regions.

Coordinated spatial organization of basal ganglia structures revealed by dopamine subtype projectome mapping

The paper maps dopamine subtype projections in the basal ganglia to reveal spatially distinct domains and their correlation with striatal neuron subclasses and cortical inputs.

Multi-scale microenvironment covariance for unsupervised spatial domain identification

The paper introduces CoSMIM, a method for spatial domain identification that uses multi-scale gene-gene covariance matrices, achieving top performance on multiple benchmark datasets.

The U6 snRNA capping enzyme Amus/MePCE is required for the stability of U6atac and the processing of introns with features of both major and minor classes

The paper identifies a role for Amus/MePCE in stabilizing U6atac and shows that some minor introns require both major and minor splicing pathways for processing.