Single-cell and spatial transcriptomics

Pathway-Centric Visualization of Cell-Cell Communication in Single-Cell Transcriptomics Data

The paper introduces scVizComm, a web tool for visualizing cell-cell communication in single-cell transcriptomics data with pathway-centric prioritization.

Scalable, fast and accurate differential gene expression testing from millions of cells of multiple patients

This paper introduces a Bayesian framework for differential gene expression analysis that scales to over 10 million cells and integrates data from multiple patients.

Evaluation of analysis modes for RNA coexpression in single-cell and bulk tissue

This study evaluates coexpression analysis methods in single-cell and bulk data, finding that xCell provides more replicable and biologically interpretable results than other modes.

Morpho-FM: spatial molecular reconstruction from routine H&E histology using transcriptomic foundation-model priors

Morpho-FM predicts spatial gene expression from H&E images using a pretrained transcriptomic foundation model, achieving strong performance in prostate and kidney cancer datasets.

Elucidating the Design Space of Generative Models for Single-Cell Perturbation Prediction

This paper introduces eVAE, a discrete-latent model for single-cell perturbation prediction, achieving state-of-the-art results on multiple metrics and outperforming existing methods in perturbation ranking.

Population-associated molecular variation in histologically normal breast tissue is context-dependent and associated with distinct transcriptional states

The paper identifies context-dependent transcriptional states in normal breast tissue that show population-associated differences, with distinct biological programs in specific tissue contexts.

scMagnifier: resolving fine-grained cell subtypes via GRN-informed perturbations and consensus clustering

scMagnifier improves fine-grained cell subtype resolution in scRNA-seq by using GRN-informed perturbations and consensus clustering, enhancing accuracy in both single and multi-batch data.

Benchmarking gene expression reconstruction from single-cell latent representations

The paper benchmarks gene expression reconstruction from single-cell latent representations, finding autoencoders perform best at low dimensionality and foundation models depend on decoder architecture.

Deciphering shared and divergent tissue architectures from cross-species spatial transcriptomics

This paper introduces STACAME, a framework for analyzing cross-species spatial transcriptomics data to identify shared and divergent tissue architectures across species.

Disentangling covariate effects on single cell-resolved epigenomes with DeepDive

DeepDive disentangles covariate effects on single-cell epigenomes, enabling counter-factual analyses and identifying diabetes-linked beta cell subtypes.

Correcting spatial transcriptomics data affected by a prevalent transcript leakage problem across platforms, species, and tissues

The paper identifies a widespread transcript leakage issue in spatial transcriptomics and introduces DeLeakage, a Bayesian method that improves data cleaning and cell-type annotation.

Multicellular Spatial Programs Define the Histopathological Architecture of Meningioma

This study identifies multicellular spatial molecular programs in meningiomas using multi-omic data and develops a model to infer these programs from histopathology.

Steller: a high-resolution platform for spatial clonal tracing of mammalian brain development

Steller improves clonal detection sensitivity in spatial transcriptomics and reveals region-specific spatial clonal architectures in the developing mouse forebrain.

Multimodal Hypersampling of the adult human heart resolves tissue-specific cell states and disease-associated variants

This paper creates a detailed heart atlas using multimodal data to identify cell states and disease-associated genetic variants in specific heart regions.

Single-section spatial hypoxia-cytotoxic associations do not consistently reproduce across breast cancer patients

The paper evaluates whether spatial associations between hypoxia and cytotoxic gene activity in breast cancer sections are consistent across patients, finding they are not.

DOMINO: graph diffusion learning identifies spatial domain structures with enhanced accuracy and scalability

DOMINO identifies spatial domains in spatial transcriptomic data with improved accuracy and scalability, outperforming existing methods on large datasets.

Single-nucleus multiomic analysis reveals modulation of the gene regulatory circuit landscape in pituitary cell types during mouse estrous cycle.

The paper uses single-nucleus multiomics to study pituitary cell changes during the mouse estrous cycle, finding stage-dependent gene regulatory circuits and validated ETS2-driven gene expression patterns.

scTimeBench: A streamlined benchmarking platform for single-cell time-series analysis

scTimeBench benchmarks single-cell time-series analysis methods across forecast accuracy, embedding coherence, and lineage fidelity using eight datasets from four species.

Cross-linked volumetric DNA microscopy for dense molecular-network phenotyping in intact tissue

This paper introduces xVDM, a method for three-dimensional molecular phenotyping in intact tissues, achieving dense molecular networks and broader transcriptome recovery than traditional approaches.

Robust integration of weakly anchored spatial multi-omics

This paper introduces SpaWeaver, a framework for robust spatial multi-omics integration using weak anchors, showing improved performance in handling real-world challenges and enabling new biological insights.

Deep Cellular and Spatial Profiling of the Mouse Spinal Cord Reveals Sex-Specific Neuron Types and the Ascending Projection Neuron Repertoire

The paper uses spatial transcriptomics and multiomic profiling to identify sex-specific neuron types and their functional roles in the mouse spinal cord.

Same-section spatial metabolo-transcriptomics using Stereo-meta-seq reveals DHA-driven kidney maturation

This study introduces Stereo-meta-seq to integrate spatial metabolomics and transcriptomics in human kidney development, revealing DHA's role in proximal tubule maturation.

scIsoAgent enables autonomous isoform-resolved characterization and sequence-informed interpretation of long-read single-cell transcriptomes

scIsoAgent improves long-read single-cell RNA-seq analysis by creating reproducible, isoform-resolved workflows and linking sequence data to functional hypotheses.

Lineage Memory and Convergent Adaptation Dictate the Single-Cell and Spatial Architecture of Brain Malignancies

This study constructs the largest single-cell atlas of brain malignancies, revealing lineage memory, convergent adaptation, and spatial architecture shaping tumor microenvironments and clinical outcomes.

Inferring Cell Fate Trajectories in Time-Resolved Metabolic RNA Labeling data

The paper introduces FLOWSATATE, a trajectory inference method using time-resolved RNA labeling data to model cell fate dynamics and predict future states.

Single-cell map of the healthy human immune system across the lifespan reveals unique infant immune signatures

The paper maps the human immune system across the lifespan using scRNA-seq and snATAC-seq, revealing unique infant immune signatures and age-related changes in immune cell populations.

Somatic variant detection in normal tissues from single-cell sequencing data

This study evaluates somatic variant calling in normal tissues using single-cell RNA and ATAC sequencing, showing Monopogen outperforms other tools in accuracy and sensitivity.

Cellfm-datasets: A Unified Data Infrastructure for Single-Cell and Spatial Transcriptomics Foundation Model Pretraining

The paper introduces Cellfm-datasets, a data infrastructure for efficient pretraining of cell foundation models using single-cell and spatial transcriptomics data.

PertDiffBench: Benchmarking Diffusion Models for Single-Cell Perturbation Response Prediction

PertDiffBench benchmarks diffusion models for predicting transcriptional responses to perturbations in single-cell and bulk RNA-seq data, showing mixed performance across different tasks and settings.

The Logic of Thalamic Inputs onto the Molecular Taxonomy of Cortical Neurons Reveals a Visual Hierarchy

The paper maps thalamic inputs onto molecularly defined cortical neurons in mice, revealing a visual hierarchy through bottom-up and top-down signatures.