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...

Ribosome Profiling

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...

You might also read

Related Articles

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

Sort by

Same author

Microbial antagonists for preserving pear quality: A review on biocontrol strategies against fungal spoilage.

International journal of food microbiology·2026

Same author

Controlled encapsulation and droplet size prediction in two-step microfluidic double emulsions.

Lab on a chip·2026

Same author

Time poverty and access-based consumption: Convenience gains and risk blindness.

British journal of psychology (London, England : 1953)·2026

Same author

High-specificity kilobase-level multiplex PCR enabled by graphene oxide-dendrimer-encapsulated gold nanoparticles.

Journal of materials chemistry. B·2026

Same author

Injectable porous nanocomposite microgel assemblies engineered via a triple-dynamic crosslinking strategy for vascularized bone regeneration.

Materials today. Bio·2026

Same author

A novel peak-searching method for multiple radioisotopes based on deep learning.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine·2026

Search research articles

Related Experiment Video

Updated: Oct 6, 2025

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

A deep generative model for multi-view profiling of single-cell RNA-seq and ATAC-seq data.

Gaoyang Li¹, Shaliu Fu^2,3, Shuguang Wang^2,3

¹Tongji University Cancer Center, Shanghai Tenth People's Hospital of Tongji University, Tongji University, Shanghai, 200092, China.

|January 13, 2022

Summary

We developed the single-cell Multi-View Profiler (scMVP), a deep generative model for multi-modal single-cell sequencing data. scMVP handles gene expression and chromatin accessibility, improving cell clustering and data imputation for biological discovery.

More Related Videos

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

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

Published on: May 23, 2018

Related Experiment Videos

Last Updated: Oct 6, 2025

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

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

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

Published on: May 23, 2018

Area of Science:

Computational biology
Genomics
Single-cell analysis

Background:

Simultaneous measurement of gene expression and chromatin accessibility in single cells provides a comprehensive view of cellular states.
Existing computational methods struggle with the sparsity and multi-modal nature of such data.
Techniques like SNARE-seq, sci-CAR, Paired-seq, SHARE-seq, and 10X Genomics Multiome generate valuable but complex datasets.

Purpose of the Study:

To introduce the single-cell Multi-View Profiler (scMVP), a novel deep generative model.
To enable robust analysis of joint gene expression and chromatin accessibility data from various single-cell multi-omic techniques.
To address data sparsity and improve downstream analyses such as cell clustering and regulatory element identification.

Main Methods:

Developed a multi-modal deep generative model, scMVP.
scMVP creates common latent representations for integrated analysis.
The model performs imputation for differential analysis and cis-regulatory element identification.

Main Results:

scMVP effectively reduces dimensionality, clusters cells, and infers developmental trajectories using common latent embeddings.
The model successfully imputes sparse data, enhancing differential analysis.
scMVP accurately identifies cell groups across different joint profiling techniques.
Demonstrated the model's advantages on several realistic multi-omic datasets.

Conclusions:

scMVP offers a powerful computational framework for analyzing complex single-cell multi-omic data.
The model mitigates data sparsity and improves the accuracy of cell group identification.
scMVP facilitates deeper biological insights from joint gene expression and chromatin accessibility measurements.