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

Epistasis Analysis01:09

Epistasis Analysis

5.0K
Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
5.0K
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

13.4K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
13.4K

You might also read

Related Articles

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

Sort by
Same author

Insights into seasonal nitrogen dynamics and microbial responses in dual-mode stormwater-lake water biofiltration.

The Science of the total environment·2025
Same author

Optimal Control of Directional False Discovery Rates in Large-Scale Testing.

Statistics in medicine·2025
Same author

Directional false discovery rate control in large-scale multiple comparisons.

Journal of applied statistics·2024
Same author

Online monitoring of high-dimensional binary data streams with application to extreme weather surveillance.

Journal of applied statistics·2022
Same author

Enhancing Built-in Electric Field via Molecular Dipole Control in Conjugated Microporous Polymers for Boosting Charge Separation.

ACS applied materials & interfaces·2022
Same author

Principal Amalgamation Analysis for Microbiome Data.

Genes·2022
Same journal

Comparing Adaptive Interventions under a General Sequential Multiple Assignment Randomized Trial Design via Multiple Comparisons with the Best.

Journal of statistical planning and inference·2026
Same journal

Variable Selection in Ultra-high Dimensional Feature Space for the Cox Model with Interval-Censored Data.

Journal of statistical planning and inference·2026
Same journal

On semi-supervised estimation using exponential tilt mixture models.

Journal of statistical planning and inference·2025
Same journal

Regression-Assisted Bayesian Record Linkage for Causal Inference in Observational Studies with Covariates Spread Over Two Files.

Journal of statistical planning and inference·2024
Same journal

Efficient inference of parent-of-origin effect using case-control mother-child genotype data.

Journal of statistical planning and inference·2024
Same journal

Information content of stepped wedge designs under the working independence assumption.

Journal of statistical planning and inference·2023
See all related articles
  1. Home
  3. Distributed Eqtl Analysis With Auxiliary Information.
  1. Home
  3. Distributed Eqtl Analysis With Auxiliary Information.

Related Experiment Video

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

13.0K

Distributed eQTL analysis with auxiliary information.

Zhiwen Fang1, Gen Li2, Wendong Li3

  • 1KLATASDS-MOE, School of Statistics, East China Normal University, Shanghai, China.

Journal of Statistical Planning and Inference
|January 24, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

This study introduces a new statistical method to improve the detection of expression quantitative trait loci (eQTLs) in a specific tissue by leveraging data from other tissues. The approach enhances eQTL discovery power by integrating shared and distinct genetic effects across multiple tissues.

Keywords:
Auxiliary informationDistributed computingMultiple testingeQTL analysis

More Related Videos

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
08:27

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

3.7K
Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

3.5K

Related Experiment Videos

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

13.0K
Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
08:27

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

3.7K
Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

3.5K

Area of Science:

  • Genetics
  • Statistical Genomics
  • Bioinformatics

Background:

  • Expression quantitative trait locus (eQTL) analysis links genetic variations to gene expression levels.
  • Existing methods often analyze tissues independently or focus on shared eQTLs, neglecting valuable auxiliary tissue information.
  • There is a need for methods that improve eQTL detection in a target tissue by utilizing data from related tissues.

Purpose of the Study:

  • To develop a novel statistical framework for enhanced eQTL detection in a target tissue.
  • To effectively integrate information from auxiliary tissues to boost statistical power.
  • To provide efficient computational approaches for large-scale multi-tissue eQTL analysis.

Main Methods:

  • Proposed a statistical framework incorporating shared and specific effects across multiple tissues.
  • Developed data-driven and distributed computing strategies for efficient implementation.
  • Applied the method to simulated data and real-world GTEx project data.

    • Main Results:

    • The novel framework significantly improves the power of eQTL detection compared to existing methods.
    • Simulation studies confirmed the method's efficacy in identifying true eQTLs.
    • Real data analysis revealed new insights into tissue-specific and shared eQTLs within the GTEx dataset.

    Conclusions:

    • The proposed method offers a powerful approach for eQTL discovery by leveraging multi-tissue information.
    • Efficient implementation strategies enable its application to large genomic datasets.
    • This framework advances our understanding of the genetic architecture of gene expression across diverse human tissues.