Article

Validation of Morphology-Guided Computational Enhancement for Single-Cell Resolution Spatial Transcriptomics

2025-07-07

Abstract excerpt

Spatial transcriptomics technologies face a fundamental trade-off between transcriptomic breadth and spatial resolution, with widely-used platforms like 10x Visium capturing multiple cells per spot, limiting single-cell insights. Current computational deconvolution methods attempt to address this limitation but uniformly suffer from reference dependency, platform effects, and complete neglect of tissue morphology....

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 992efd68-2e0e-5f8e-9ffa-ca00767ab4b5
DOI: 10.1101/2025.07.03.663047

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Validation of Morphology-Guided Computational Enhancement for Single-Cell Resolution Spatial TranscriptomicsDOI 10.1101/2025.07.03.663047Read

STCS: A Platform-Agnostic Framework for Cell-Level Reconstruction in Sequencing-Based Spatial TranscriptomicsSemantic proximity Read

SPARKLE: evidence-constrained correction of local RNA leakage in high-resolution spatial transcriptomicsSemantic proximity Read

A transcriptomic-driven segmentation and cell simulation framework for high-resolution spatial transcriptomics and cell-cell communicationSemantic proximity Read

Systematic Benchmarking of High-Throughput Subcellular Spatial Transcriptomics PlatformsSemantic proximity Read

STHELAR, a multi-tissue dataset linking spatial transcriptomics and histology for cell type annotationSemantic proximity Read

Mitigation of multi-scale biases in cell-type deconvolution for spatially resolved transcriptomics using HarmoDeconSemantic proximity Read

Bin2cell reconstructs cells from high resolution Visium HD dataSemantic proximity Read

Φ-Space ST: a platform-agnostic method to identify cell states in spatial transcriptomics studiesSemantic proximity Read

MAST-Decon: Smooth Cell-type Deconvolution Method for Spatial Transcriptomics DataSemantic proximity Read

Sparse deconvolution of cell type medleys in spatial transcriptomicsSemantic proximity Read

Spatial gene expression at single-cell resolution from histology using deep learning with GHISTSemantic proximity Read

STHD: probabilistic cell typing of single Spots in whole Transcriptome spatial data with High DefinitionSemantic proximity Read