Article

Integrative cross-sample alignment and spatially differential gene analysis for spatial transcriptomics

2025-06-06

Abstract excerpt

<h4>ABSTRACT</h4> Spatial transcriptomics (ST) technologies offer rich spatial context for gene expression, with varying spatial resolutions and gene coverages. However, aligning and comparing multiple ST slices, whether derived from the same or different platforms, remains challenging due to nonlinear distortions and limited spatial overlap caused by tissue processing. We present CODA, an integrative framework f...

Topics

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

Identifiers and source

Literature Corpus work: 02d2ccfb-912e-59f6-8554-155903eace91
DOI: 10.1101/2025.06.05.653933

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Integrative cross-sample alignment and spatially differential gene analysis for spatial transcriptomicsDOI 10.1101/2025.06.05.653933Read

JADE: Joint Alignment and Deep Embedding for Multi-Slice Spatial TranscriptomicsSemantic proximity Read

OT-knn: a neighborhood-aware optimal transport framework for aligning spatial transcriptomics dataSemantic proximity Read

Towards Cross-Sample Alignment for Multi-Modal Representation Learning in Spatial TranscriptomicsSemantic proximity Read

Spatial pattern and differential expression analysis with spatial transcriptomic dataSemantic proximity Read

GALA: A Unified Landmark-Free Framework for Coarse-to-Fine Spatial Alignment Across Resolutions and Modalities in Spatial TranscriptomicsSemantic proximity Read

Topography Aware Optimal Transport for Alignment of Spatial Omics DataSemantic proximity Read

Cross-view graph neural networks for spatial domain identification by integrating gene expression, spatial locations with histological imagesSemantic proximity Read

Riemannian Metric Learning for Alignment of Spatial MultiomicsSemantic proximity Read

Integrating spatial transcriptomics data across different conditions, technologies, and developmental stagesSemantic proximity Read

Inferring single-cell resolution spatial gene expression via fusing spot-based spatial transcriptomics, location and histology using GCNSemantic proximity Read

Randomized Spatial PCA (RASP): a computationally efficient method for dimensionality reduction of high-resolution spatial transcriptomics dataSemantic proximity Read

Deciphering shared and divergent tissue architectures from cross-species spatial transcriptomicsSemantic proximity Read