Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Continuous Size-Based Particle Separation Using Inertial Force and Deterministic Lateral Displacement.

Micromachines·2026

Same author

Interfacial Energy Balance Governs Initial Cell Spreading Dynamics.

Langmuir : the ACS journal of surfaces and colloids·2025

Same author

Electroactive Asymmetric Dressing for Spatiotemporal Deep Burn Scarless Healing and Management.

Advanced healthcare materials·2025

Same author

Extended replicative lifespan of primary resting T cells by CRISPR/dCas9-based epigenetic modifiers and transcriptional activators.

Cellular and molecular life sciences : CMLS·2024

Same author

Mechanical Constraints in Tumor Guide Emergent Spatial Patterns of Glioblastoma Cancer Stem Cells.

Mechanobiology in medicine·2024

Same author

Recent progress of organ-on-a-chip towards cardiovascular diseases: advanced design, fabrication, and applications.

Biofabrication·2023

Search research articles

Related Experiment Video

Updated: Jul 6, 2026

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using a

Zhongning Jiang¹, Wei Huang¹, Raymond H W Lam^2,3

¹Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, 999077, China.

BMC Bioinformatics

|December 19, 2024

Summary

Spall, a new computational method, accurately maps cell types in tissues by integrating single-cell RNA sequencing (scRNA-seq) and spatially resolved transcriptomics (SRT) data. It effectively balances spatial patterns with cell characteristics, improving tissue structure analysis.

Keywords:

Cell type proportion Decomposition Graph neural network Spatially resolved transcriptomics Tissue structure

More Related Videos

Laser-Capture Microdissection RNA-Sequencing for Spatial and Temporal Tissue-Specific Gene Expression Analysis in Plants

Laser-Capture Microdissection RNA-Sequencing for Spatial and Temporal Tissue-Specific Gene Expression Analysis in Plants

Published on: August 5, 2020

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

Related Experiment Videos

Last Updated: Jul 6, 2026

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Laser-Capture Microdissection RNA-Sequencing for Spatial and Temporal Tissue-Specific Gene Expression Analysis in Plants

Laser-Capture Microdissection RNA-Sequencing for Spatial and Temporal Tissue-Specific Gene Expression Analysis in Plants

Published on: August 5, 2020

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

Area of Science:

Genomics
Computational Biology
Bioinformatics

Background:

Spatially resolved transcriptomics (SRT) advances tissue structure characterization.
Existing decomposition methods struggle to balance spatial continuity with cell-specific data preservation.
Accurate cellular distribution inference is crucial for understanding tissue organization.

Purpose of the Study:

To develop a novel decomposition network, Spall, for accurate cell type proportion inference.
To integrate single-cell RNA sequencing (scRNA-seq) and SRT data effectively.
To overcome limitations of existing methods in balancing spatial and cellular characteristics.

Main Methods:

Proposed Spall, a novel decomposition network integrating scRNA-seq and SRT data.
Introduced the GATv2 module with a dynamic attention mechanism to capture spot relationships.
Incorporated skip connections to preserve cell-specific information, aiding rare cell type prediction.

Main Results:

Spall outperforms state-of-the-art methods in reconstructing cell distribution patterns across multiple datasets.
Successfully revealed tumor heterogeneity in human pancreatic ductal adenocarcinoma.
Delineated complex tissue structures, including the mouse cerebral cortex and cerebellum.

Conclusions:

Spall accurately infers cell type proportions and improves spatial analysis.
Provides reliable low-dimensional embeddings for downstream analyses.
Offers new avenues for deciphering complex tissue structures and heterogeneity.