Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

RNA-seq03:21

RNA-seq

11.5K
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...
11.5K
Ribosome Profiling02:24

Ribosome Profiling

4.0K
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...
4.0K

You might also read

Related Articles

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

Sort by
Same author

An encyclopedia of human enhancer-gene regulatory interactions.

Nature·2026
Same author

Teaching an old dog new cells.

Nature methods·2026
Same author

Sequence design for three-dimensional genome folding using Akita Semifreddo.

bioRxiv : the preprint server for biology·2026
Same author

Parameter-efficient fine-tuning enables scalable transfer of regulatory sequence models to novel contexts.

Genome biology·2026
Same author

Predicting dynamic expression patterns in budding yeast with a fungal DNA language model.

bioRxiv : the preprint server for biology·2025
Same author

Rewriting regulatory DNA to dissect and reprogram gene expression.

Cell·2025

Related Experiment Video

Updated: Dec 17, 2025

Single-cell RNA Sequencing and Analysis of Human Pancreatic Islets
11:34

Single-cell RNA Sequencing and Analysis of Human Pancreatic Islets

Published on: July 18, 2019

16.9K

Solo: Doublet Identification in Single-Cell RNA-Seq via Semi-Supervised Deep Learning.

Nicholas J Bernstein1, Nicole L Fong1, Irene Lam1

  • 1Calico Life Sciences LLC, South San Francisco, CA, USA.

Cell Systems
|June 28, 2020
PubMed
Summary

Solo, a new deep learning tool, accurately identifies doublets in single-cell RNA sequencing data. This method improves the reliability of gene expression analysis by distinguishing true single cells from multiplets.

Keywords:
deep learningdoubletsemi-supervised learningsingle-cell RNA-seq

More Related Videos

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

18.9K
Low-input Nucleus Isolation and Multiplexing with Barcoded Antibodies of Mouse Sympathetic Ganglia for Single-nucleus RNA Sequencing
10:44

Low-input Nucleus Isolation and Multiplexing with Barcoded Antibodies of Mouse Sympathetic Ganglia for Single-nucleus RNA Sequencing

Published on: March 23, 2022

4.7K

Related Experiment Videos

Last Updated: Dec 17, 2025

Single-cell RNA Sequencing and Analysis of Human Pancreatic Islets
11:34

Single-cell RNA Sequencing and Analysis of Human Pancreatic Islets

Published on: July 18, 2019

16.9K
Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

18.9K
Low-input Nucleus Isolation and Multiplexing with Barcoded Antibodies of Mouse Sympathetic Ganglia for Single-nucleus RNA Sequencing
10:44

Low-input Nucleus Isolation and Multiplexing with Barcoded Antibodies of Mouse Sympathetic Ganglia for Single-nucleus RNA Sequencing

Published on: March 23, 2022

4.7K

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Single-cell RNA sequencing (scRNA-seq) provides high-resolution cellular gene expression data.
  • Technical artifacts, such as doublets (two or more cells sharing a barcode), compromise data integrity and lead to inaccurate biological inferences.

Purpose of the Study:

  • To develop a novel computational method for accurate doublet detection in scRNA-seq data.
  • To improve the reliability and accuracy of single-cell gene expression profiling.

Main Methods:

  • Developed Solo, a semi-supervised deep learning approach utilizing a variational autoencoder for unsupervised cell embedding.
  • Integrated a feed-forward neural network classifier trained on simulated doublets to distinguish true single cells from multiplets.
  • Applied Solo to observed scRNA-seq data for doublet identification.

Main Results:

  • Solo demonstrates superior accuracy in identifying doublets compared to existing methods.
  • The deep learning framework effectively distinguishes simulated doublets from real single-cell data.
  • Solo can enhance existing experimental doublet detection methods for improved data purification.

Conclusions:

  • Solo offers a robust and accurate computational solution for doublet detection in scRNA-seq experiments.
  • This method facilitates more reliable downstream analyses by ensuring data purity.
  • Solo is freely available, promoting wider adoption and advancement in single-cell genomics research.