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

Genetic Screens02:46

Genetic Screens

5.9K
Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...
5.9K

You might also read

Related Articles

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

Sort by
Same author

Dual tumour-myeloid targeting of glioblastoma with GPNMB CAR-T cells.

Nature·2026
Same author

Mapping the genetic landscape of the DNA damage response with Cas12a-based combinatorial knockout screens.

bioRxiv : the preprint server for biology·2026
Same author

Orobas: A computational approach for scoring and analysis of quantitative chemical-genetic interactions from CRISPR-Cas9 screens.

STAR protocols·2026
Same author

uPAR is highly expressed in recurrent glioblastoma and represents a candidate CAR T cell target.

Science translational medicine·2026
Same author

Global genetic interaction network of a human cell maps conserved principles and informs functional interpretation of gene co-essentiality profiles.

Cell·2026
Same author

Generation of Allogeneic CAR-T Circumvents Functional Deficits in Patient-Derived Autologous Product for Glioblastoma.

International journal of cancer·2026

Related Experiment Video

Updated: Mar 22, 2026

Pooled CRISPR-Based Genetic Screens in Mammalian Cells
09:05

Pooled CRISPR-Based Genetic Screens in Mammalian Cells

Published on: September 4, 2019

23.5K

BAGEL: a computational framework for identifying essential genes from pooled library screens.

Traver Hart1, Jason Moffat2,3

  • 1Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA. traver.hart@gmail.com.

BMC Bioinformatics
|April 17, 2016
PubMed
Summary

New Bayesian Analysis of Gene EssentiaLity (BAGEL) software significantly improves gene knockout screen analysis. It enhances sensitivity and reduces runtime for identifying essential genes in human cell lines.

Keywords:
CRISPRCancerEssential genesFunctional genomicsGenetic screens

More Related Videos

Competitive Genomic Screens of Barcoded Yeast Libraries
11:59

Competitive Genomic Screens of Barcoded Yeast Libraries

Published on: August 11, 2011

18.9K
Author Spotlight: Finding New Therapeutic Targets for Malignant Peripheral Nerve Sheath Tumor Through Genome-Scale shRNA Screens
09:33

Author Spotlight: Finding New Therapeutic Targets for Malignant Peripheral Nerve Sheath Tumor Through Genome-Scale shRNA Screens

Published on: August 25, 2023

1.8K

Related Experiment Videos

Last Updated: Mar 22, 2026

Pooled CRISPR-Based Genetic Screens in Mammalian Cells
09:05

Pooled CRISPR-Based Genetic Screens in Mammalian Cells

Published on: September 4, 2019

23.5K
Competitive Genomic Screens of Barcoded Yeast Libraries
11:59

Competitive Genomic Screens of Barcoded Yeast Libraries

Published on: August 11, 2011

18.9K
Author Spotlight: Finding New Therapeutic Targets for Malignant Peripheral Nerve Sheath Tumor Through Genome-Scale shRNA Screens
09:33

Author Spotlight: Finding New Therapeutic Targets for Malignant Peripheral Nerve Sheath Tumor Through Genome-Scale shRNA Screens

Published on: August 25, 2023

1.8K

Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • CRISPR-Cas9 gene knockout screens offer advancements over RNA interference for mammalian cell studies.
  • Analyzing the large datasets generated by these screens requires novel computational methods.

Purpose of the Study:

  • To develop and validate a new computational method for analyzing CRISPR-Cas9 pooled library gene knockout screens.
  • To improve the accuracy and efficiency of identifying essential genes from screen data.

Main Methods:

  • Developed Bayesian Analysis of Gene EssentiaLity (BAGEL), a supervised machine learning approach.
  • Utilized gold-standard reference sets of essential and nonessential genes for training and validation.
  • Implemented computational optimizations to enhance processing speed.

Main Results:

  • BAGEL demonstrates significantly higher sensitivity in identifying essential genes compared to existing methods.
  • Computational optimizations resulted in an order of magnitude reduction in analysis runtime.
  • Identified approximately 2000 fitness genes in human cell line screens at a 5% false discovery rate.

Conclusions:

  • BAGEL represents a major advance for analyzing pooled library knockout screens.
  • The method exhibits high sensitivity and specificity across diverse experimental conditions and reagents.
  • Enables more robust identification of fitness genes in large-scale genetic screens.