Single-cell and spatial transcriptomics

spaCraft: calibrated power analysis and sample-size planning for multi-sample spatial transcriptomics

spaCraft provides calibrated power analysis and sample-size planning for multi-sample spatial transcriptomics by integrating domain recovery and clustering uncertainty.

Analysis of multicellular anatomical structures from spatial omics data using sosta

The paper introduces a method for analyzing multicellular anatomical structures from spatial omics data and provides an open-source tool for this purpose.

A single-nucleus and spatial transcriptomic atlas of the Syrian hamster preoptic area across hibernation states

This study creates a transcriptomic atlas of the Syrian hamster preoptic area using snRNA-seq and spatial transcriptomics, comparing seasonal and hibernation states.

Three-dimensional Virtual Adult Cardiomyocyte Transcriptomics

This paper introduces 3D-VirtualCM, a method to reconstruct full cardiomyocyte transcriptomes from spatial transcriptomic sections, revealing spatial and transcriptional heterogeneity in infarcted mouse hearts.

dictyExpress: an integrated browser for bulk and single-cell Dictyostelium transcriptomics

dictyExpress 3.0 integrates bulk and single-cell transcriptomics data for Dictyostelium, offering interactive visualizations and cross-modal analysis.

PhenoMapR: scalable mapping of sample phenotypes to single-cell, spatial, and bulk transcriptomics data

PhenoMapR maps bulk expression phenotypes to single-cell and spatial transcriptomics data to identify biologically relevant cellular populations and spatial niches.

Breast cancer through the lens of whole transcriptome spatial imaging

The paper uses spatial transcriptomics to analyze a breast tumor, identifying spatially distinct biological processes and potential therapeutic targets.

Selective collateralization of transcriptomically distinct neurons organizes visual-stream output from the primary visual cortex

The paper maps gene expression and axonal projections of neurons in the mouse primary visual cortex to reveal how retinotopy and cell-type-specific collateralization organize visual-stream output.

A Systematic Comparison of Single-Cell Perturbation Response Prediction Models

The paper benchmarks 13 models for predicting single-cell perturbation responses across 25 datasets, finding performance varies with perturbation effect size and evaluation metric.

Independent benchmark of H&E-based gene expression prediction in skin

This study benchmarks H&E-based gene expression prediction methods in skin tissue, finding poor performance overall and limited utility for single-cell analysis.

SPARKLE: evidence-constrained correction of local RNA leakage in high-resolution spatial transcriptomics

SPARKLE corrects local RNA leakage in spatial transcriptomics by using spatial evidence within each sample, improving cell-type localization and communication inference.

A high-resolution blood immune cell doublet atlas via imaging spectral cytometry

Image-based gating on an imaging spectral cytometer resolves 12 high-purity immune doublet types in human blood; in tuberculosis, doublet frequencies are unchanged but tightly contacting T cell-monocyte doublets increase.

Impact of single-cell RNA reference selection for the deconvolution of breast cancer spatial transcriptomics datasets

This study evaluates how reference selection affects deconvolution accuracy in breast cancer spatial transcriptomics datasets, finding that small references can be effective and that perfect reference-ST matching improves results.

Reconstructing signaling histories of single cells via perturbation screens and transfer learning

The paper develops a framework combining perturbation screens and transfer learning to reconstruct signaling histories in cells and optimize differentiation protocols.

Atlas-scale single-cell analysis beyond in-memory paradigm with scAtlasPy

scAtlasPy enables efficient analysis of large single-cell atlases by using disk-resident computing, achieving high speed and low memory usage compared to existing tools.

scFLAME: a unified generative model for interpretable clustering, hierarchical structure discovery and marker-gene identification in single-cell RNA-seq data

scFLAME is a generative model that unifies clustering, marker-gene identification, and hierarchical structure discovery in scRNA-seq data, achieving state-of-the-art accuracy and scalability.

Single-Cell Indel Detection Enhances Genetic Ancestry and Cellular Lineage Analysis

Monopogen-Indel calls germline indels from single-cell and single-nucleus RNA data at 73.0% (retina) and ~87% (ovarian cancer) WGS-validated precision, though no single-cell somatic indel matched a WGS somatic indel.

Systematic Comparison of 10X Genomics and Parse Single Cell RNA Technologies across PBMC and CD8+ TEMRA Cells

Side-by-side PBMC and CD8+ TEMRA profiling shows Parse favors longer transcripts but underdetects cytotoxic genes (GNLY, PRF1, GZMB), so 10X Chromium better resolves TEMRA subsets.

platpy: A spatial-first framework for multi-layer spatial transcriptomic analysis

platpy provides a spatial-first framework for analyzing spatial transcriptomic data, improving efficiency and reducing errors in multi-layer spatial analysis.

SCG: Spatially Co-Expressed Gene Identification through Spatially Varying Networks

This paper introduces SCR, a Bayesian framework for estimating spatially-resolved gene co-expression networks to identify spatially co-expressed genes as potential biomarkers and therapeutic targets.

Evaluating the Robustness of Path-Preservation Benchmarks for Dimensionality Reduction Across Point-Density Thresholds: Linear and Cyclic Single-Cell Trajectories

This paper evaluates how dimensionality reduction methods affect trajectory geometry by testing their path-preservation across different point-density thresholds on linear and cyclic single-cell datasets.

Global tree encoding of atlas-scale single-cell genomics

The paper introduces MILK, a framework for organizing single-cell genomic data into tree representations, enabling scalable analysis and preserving information across large datasets.

AltraFlowSOM: A Semi-Supervised Framework for Imaging Mass Cytometry Phenotyping

AltraFlowSOM improves IMC phenotyping by combining semi-supervised learning with self-organizing maps, outperforming unsupervised and supervised methods in clustering and rare population detection.

Modelling interpretable patient-level representationsfrom structured and simple multimodal data

The paper introduces FACTMx, a variational framework that jointly models structured and simple patient-level data to learn interpretable representations, showing improved performance in simulations and applications to cancer and cardiovascular cohorts.

Systematic benchmarking of commercial workflows for isoform-resolved single-nucleus transcriptomics

This study benchmarks four commercial LR snRNA-seq workflows, finding 10x Genomics 3' and 5' to be the most balanced for isoform-resolved single-nucleus transcriptomics.

Spatial multi-omics and single-cell transcriptomics uncover senescence-associated cellular programs during colon adenoma to cancer progression

The paper uses spatial multi-omics and single-cell transcriptomics to identify senescence-associated programs in colon adenoma to cancer progression, finding GDF15 mediates senescence-stemness coupling and immune exclusion.

An Integrated Single-Nucleus Atlas Resolves Cell-Type-Specific Programs and Molecular Subtypes in Alzheimer's Disease

The paper constructs a single-nucleus transcriptomic atlas of Alzheimer's disease and identifies cell-type-specific molecular subtypes and therapeutic targets using a new framework.

Unifying physical and molecular coordinate systems across modalities in spatial biology

The paper introduces MAPS, a platform for unifying physical and molecular coordinates across modalities in spatial biology, demonstrating its effectiveness on diverse datasets and applications.

Cell-type-resolved somatic variant discovery from bulk long-read sequencing

SniffCell assigns somatic variants to cell types using DNA methylation from bulk long-read sequencing, revealing cell-type-specific mutations in human tissues.

Cross-domain confidence reliability and remappability of frozen single-cell representations

The paper evaluates the reliability of confidence measures from single-cell models on new data and shows that raw confidence scores are unreliable, requiring recalibration with target-specific labels.