Single-cell and spatial transcriptomics

Pycea: a scverse toolkit for single-cell lineage tracing analysis

Pycea provides a toolkit for analyzing single-cell lineage tracing data, integrating with Scanpy and offering visualization and statistical methods for lineage trees.

RNA assignment and segmentation geometry in Visium HD profiles of fibrostenotic Crohn's disease

The paper evaluates segmentation methods for reconstructing cell-like profiles from spatial transcriptomics data but finds no reliable method under the given constraints.

FateDriver: Weakly supervised dual-view graph learning for transition-specific prioritization of candidate regulators in cellular reprogramming

FateDriver prioritizes candidate regulators for specific cellular transitions using a weakly supervised dual-view graph neural network, outperforming existing methods in recovering known regulators.

Single-cell perturbation prediction near experimental reproducibility with GENESIS

GENESIS predicts single-cell perturbation responses from experimental conditions, outperforming existing models and approaching experimental reproducibility.

Single-cell foundation models transfer across deep evolutionary distances

This paper evaluates the transferability of single-cell foundation models across deep evolutionary distances using developmental atlases of Dictyostelium discoideum and Caenorhabditis elegans.

DCAF: Unifying Data Validity, Evaluation Validity and Predictive Modeling for Single-cell Perturbation Simulation

DCAF improves single-cell perturbation simulation by addressing data, evaluation, and model validity, outperforming baselines in generalization and recapitulating regulatory heterogeneity in mouse brain.

RankMap: Rank-based reference mapping for fast and robust cell type annotation in spatial and single-cell transcriptomics

RankMap improves cell type annotation in spatial and single-cell transcriptomics by using rank-based representations and multinomial regression, achieving competitive accuracy and faster runtime.

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.

Spatial Single-Cell Mapping of Transcriptional Differences Across Genetic Backgrounds in Mouse Brains

The paper introduces ATLAS, a method to map transcriptional differences across genetic backgrounds in mouse brains, revealing significant cell type distribution changes between sexes and genetic models.

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.

Digital twins forecast individual immune trajectories

The paper introduces ImmuneTwins, a digital twin framework that personalizes immune response models for individuals, improving prediction accuracy of immune trajectory changes.

flashscenic: Accelerated GRN Analysis with RegDiffusion for Large-Scale Single-Cell Data

flashscenic accelerates single-cell GRN analysis using GPU acceleration, improving speed and enabling benchmarking of integration strategies in AML data.

Live Spatial Transcriptomics Enables Longitudinal Tissue Mapping

This paper introduces Live-ST, a method for longitudinal spatial transcriptomics, and demonstrates its use in tracking drug response in melanoma tissues.

Lineage-mixed neurodevelopmental programs in pediatric sarcomas nominate tumor-selective surface antigen pairs.

This paper develops an AI framework to interpret single-cell RNA-seq data from pediatric solid tumors, identifying tumor-specific surface antigen pairs for targeted therapies.

Whole-body single-cell atlas of an adult vertebrate in homeostasis and regeneration

Region-stratified scRNA-seq of 607,370 cells plus 500-gene MERFISH maps adult Danionella cerebrum cell types body-wide, revealing fibroblast Hox and limb-identity programs and telencephalon regeneration dynamics.

Evaluation of Cross-slice Imputation for Spatial Proteomics

This paper evaluates cross-slice protein imputation methods, finding that learning-based approaches outperform alignment-based ones for imputation, while alignment-based methods are better for interpolation and 3D reconstruction.

Model-based inference of gene expression noise from single-cell RNA-sequencing data

This paper introduces a maximum-likelihood framework to estimate gene expression noise from scRNA-seq data, accounting for technical noise and cell type heterogeneity, and demonstrates its reproducibility using yeast data.

Agentic Discovery Transfer Enables Cross-Cancer Discovery at Scale

SMART, a multi-agent framework, transfers findings from single-cell RNA-sequencing cancer studies to other cancer types, identifying cross-cancer prognostic signatures and generating new hypotheses.

Joint localization and testing reveals spatial context of differential expression

This paper introduces SpaceDX, a method that jointly identifies differentially expressed genes and their spatial localization in multi-subject spatial transcriptomics data, improving detection compared to traditional approaches.

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.

Single-cell RNA-seq of amniotic fluid provides unique insight into fetal development

This study uses scRNA-seq on amniotic fluid to create a cell atlas of healthy fetal cells, revealing gestational age-related changes in cell composition and gene expression.

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.

Predicting clonal mutations from tumour spatial transcriptomics data using a graph convolutional neural network

This paper introduces SPOT-Mut, a graph convolutional neural network that predicts clonal mutations from spatial transcriptomics data, achieving high precision and recall for key driver genes.

NicheCorr: Identifying Niche-Specific Differential Gene Co-Expression in Spatial Transcriptomics

NicheCorr identifies niche-specific gene co-expression changes in spatial transcriptomics data, revealing spatially structured signaling interactions in liver and pancreatic cancer datasets.

Identification of gene kinetics patterns improves RNA velocity and cell fate prediction using JuloVelo

JuloVelo improves RNA velocity and cell fate prediction by incorporating gene kinetics patterns, outperforming existing methods across multiple differentiation programs.

Regularized logistic regression-based gene selection for functional analysis of heterogeneous scRNA-seq macrophage populations in muscle aging and regeneration.

The paper introduces DisTwiner, a method for subgroup-aware gene selection in scRNA-seq data, showing it captures biologically relevant aging pathways in macrophages.

ProtCell: a foundation model for single-cell proteomics

ProtCell connects fragmented proteomic profiles, extends information beyond measured panels, and guides more informative measurements.