Article

SiGra: Single-cell spatial elucidation through image-augmented graph transformer

2022-08-19

Abstract excerpt

<h4>ABSTRACT</h4> The recent advances in high-throughput molecular imaging push the spatial transcriptomics technologies to the subcellular resolution, which breaks the limitations of both single-cell RNA-seq and array-based spatial profiling. The latest released single-cell spatial transcriptomics data from NanoString CosMx and MERSCOPE platforms contains multi-channel immunohistochemistry images with rich infor...

Topics

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

Identifiers and source

Literature Corpus work: b7e0fa40-2531-5b61-abb5-87fadf25d1c1
DOI: 10.1101/2022.08.18.504464

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

SiGra: Single-cell spatial elucidation through image-augmented graph transformerDOI 10.1101/2022.08.18.504464Read

Hist2Cell: Deciphering Fine-grained Cellular Architectures from Histology ImagesSemantic proximity Read

Integrating cellular graph embeddings with tumor morphological features to predict in-silico spatial transcriptomics from H&E imagesSemantic proximity Read

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

Inferring single-cell spatial gene expression with tissue morphology via explainable deep learningSemantic proximity Read

Learning predictive models of tissue cellular neighborhoods from cell phenotypes with graph poolingSemantic proximity Read

PathCLAST: Pathway-Augmented Contrastive Learning with Attention for Spatial TranscriptomicsSemantic proximity Read

Predicting Gene Spatial Expression and Cancer Prognosis: An Integrated Graph and Image Deep Learning Approach Based on HE SlidesSemantic proximity Read

SORBET: Automated cell-neighborhood analysis of spatial transcriptomics or proteomics for interpretable sample classification via GNNSemantic proximity Read

stGCL: A versatile cross-modality fusion method based on multi-modal graph contrastive learning for spatial transcriptomicsSemantic proximity Read

HarveST: Heterogeneous Graph Learning Framework for Revealing Spatial Transcriptomics PatternsSemantic proximity Read

Knowledge-graph-based cell-cell communication inference for spatially resolved transcriptomic data with SpaTalkSemantic proximity Read

Spectral sparsification helps restore the spatial structure at single-cell resolutionSemantic proximity Read