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

You might also read

Related Articles

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

Sort by
Same author

Flexible and scalable inference of spatially varying correlation in spatial transcriptomics with spCorr.

Genome research·2026
Same author

CIPHER: An end-to-end framework for designing optimized aggregated spatial transcriptomics experiments.

PLoS computational biology·2026
Same author

IntegrateRigor: annotation-free integration optimization for cell identity recovery reveals cancer-immune interface niches.

bioRxiv : the preprint server for biology·2026
Same author

Cyclin-Dependent Kinase 5 Contributes to Bruton's Tyrosine Kinase Inhibitor Resistance via the IRE1α/XBP1 Axis in Mantle Cell Lymphoma.

Research square·2026
Same author

SnakeAltPromoter Facilitates Differential Alternative Promoter Analysis.

Computational and structural biotechnology journal·2026
Same author

scDesignPop generates realistic population-scale single-cell RNA-seq for power analysis, benchmarking, and privacy protection.

bioRxiv : the preprint server for biology·2026

Related Experiment Video

Updated: Jul 16, 2025

qPCRTag Analysis - A High Throughput, Real Time PCR Assay for Sc2.0 Genotyping
07:00

qPCRTag Analysis - A High Throughput, Real Time PCR Assay for Sc2.0 Genotyping

Published on: May 25, 2015

17.1K

ClipperQTL: ultrafast and powerful eGene identification method.

Heather J Zhou1, Xinzhou Ge1,2, Jingyi Jessica Li1,3,4,5

  • 1Department of Statistics and Data Science, University of California, Los Angeles, Los Angeles, CA 90095, USA.

Biorxiv : the Preprint Server for Biology
|September 11, 2023
PubMed
Summary

ClipperQTL efficiently identifies cis-eGenes (genes regulated by local genetic variants) by significantly reducing computational costs. This new method offers comparable accuracy to FastQTL but is substantially faster, accelerating eQTL analysis.

More Related Videos

High-throughput DNA Extraction and Genotyping of 3dpf Zebrafish Larvae by Fin Clipping
10:12

High-throughput DNA Extraction and Genotyping of 3dpf Zebrafish Larvae by Fin Clipping

Published on: June 29, 2018

14.1K
Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

15.3K

Related Experiment Videos

Last Updated: Jul 16, 2025

qPCRTag Analysis - A High Throughput, Real Time PCR Assay for Sc2.0 Genotyping
07:00

qPCRTag Analysis - A High Throughput, Real Time PCR Assay for Sc2.0 Genotyping

Published on: May 25, 2015

17.1K
High-throughput DNA Extraction and Genotyping of 3dpf Zebrafish Larvae by Fin Clipping
10:12

High-throughput DNA Extraction and Genotyping of 3dpf Zebrafish Larvae by Fin Clipping

Published on: June 29, 2018

14.1K
Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

15.3K

Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Identifying cis-eGenes is crucial for understanding gene regulation.
  • Existing methods like FastQTL are computationally intensive, limiting their application.
  • Alternative methods often lack the statistical power of FastQTL.

Purpose of the Study:

  • To develop a computationally efficient method for cis-eGene identification.
  • To maintain or improve the accuracy of eGene detection compared to existing gold standards.
  • To provide a faster alternative for expression quantitative trait locus (eQTL) analysis.

Main Methods:

  • Proposed ClipperQTL, a novel method for eGene identification.
  • Employed a contrastive strategy for large sample sizes (>450) to reduce permutations.
  • Utilized a conventional permutation-based approach for smaller sample sizes, similar to FastQTL.

Main Results:

  • ClipperQTL achieves performance comparable to FastQTL.
  • The contrastive strategy in ClipperQTL reduces required permutations from thousands to 20 for large datasets.
  • ClipperQTL is approximately 500 times faster with the contrastive strategy and 50 times faster with the conventional approach.

Conclusions:

  • ClipperQTL offers a significant speed improvement for eGene identification without compromising accuracy.
  • The method is suitable for both large and small sample sizes in eQTL studies.
  • An R package for ClipperQTL is publicly available.