Integrating spatial and single|cell transcriptomics data using deep ...

Integrating spatial and single-cell transcriptomics data using deep ...

We present SpatialScope, a unified approach integrating scRNA-seq reference data and ST data using deep generative models.

Integration of spatial and single-cell data across modalities with ...

For example, when one modality is protein abundance over a small antibody panel and the other is RNA expression over the whole transcriptome, ...

SpatialScope: A unified approach for integrating spatial and single ...

SpatialScope: A unified approach for integrating spatial and single-cell transcriptomics data using deep generative models. Xiaomeng Wan ...

Integrating Single Cell and Visium Spatial Gene Expression Data

Share via: Note: 10x Genomics does not provide support for community-developed tools and makes no guarantees regarding their function or ...

An introduction to spatial transcriptomics for biomedical research

maximize output from spatial transcriptomic studies using complementary data such as single-cell transcriptome reference data and auxiliary ...

Deep learning in spatially resolved transcriptomics - Oxford Academic

It involves encoding spatial data into matrices, using a hybrid adjacency matrix and a single-cell gene expression profile matrix. These ...

Deep learning applications in single-cell genomics and ...

Comprehensive mapping of tissue cell architecture via integrated single cell and spatial transcriptomics ... integration for single-cell ATAC-seq data using deep ...

Unsupervised spatially embedded deep representation of spatial ...

... spatial transcriptomics spots with single-cell transcriptomes. ... using integrated single cell, spatial and in situ analysis of FFPE tissue.

Computational solutions for spatial transcriptomics - ScienceDirect

The basis of the computational ST analysis is the solutions developed for single-cell RNA-sequencing data, with advancements taking into account the spatial ...

Integrating spatial and single-cell transcriptomics data using deep ...

The rapid emergence of spatial transcriptomics (ST) technologies is revolutionizing our understanding of tissue spatial architecture and biology.

(PDF) Integrating spatial and single-cell transcriptomics data using ...

To address these limitations, we present SpatialScope, a unified approach integrating scRNA-seq reference data and ST data using deep generative ...

Computational Strategies and Algorithms for Inferring Cellular ...

... from single-cell transcriptomics ... SpatialScope: a unified approach for integrating spatial and single-cell transcriptomics data using deep ...

Integrating spatial and single-cell transcriptomics data using deep ...

Article: Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope. Show simple item record ...

Integrating spatial and single-cell transcriptomics data using deep ...

SpatialScope provides spatial characterization of tissue structures at transcriptome-wide single-cell resolution, facilitating downstream analysis, including ...

DEEPsc: A Deep Learning-Based Map Connecting Single-Cell ...

Inferring spatial and signaling relationships between cells from single cell transcriptomic data. Nat. Commun. 11:2084. doi: 10.1038/s41467-020-15968-5.

CellContrast: Reconstructing spatial relationships in single-cell RNA ...

CellContrast is a computational method that uses gene expression data and a model trained with ST data to reconstruct the spatial relationships between cells.

Integrating Single-Cell and Spatial Transcriptomics via Deep ...

Variational Auto Encoders (VAEs), a type of deep learning model, have been used in single-cell analysis to map the gene expression of cells into a latent space, ...

METI – deep profiling of tumor ecosystems by integrating cell ...

METI is designed to provide a more comprehensive analysis of the TME by integrating three key components: spatial transcriptomics data, cell morphology.

Integrating spatial and single-cell transcriptomics data using deep ...

The rapid emergence of spatial transcriptomics (ST) technologies is revolu- tionizing our understanding of tissue spatial architecture and biology.

Integrating single-cell and spatial transcriptomics to elucidate ...

Efforts to integrate scRNA-seq with spatial transcriptomics, including emerging integrative computational methods, are reviewed, and ways to effectively ...