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

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

15.4K
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...
15.4K
Interpreting R Charts01:22

Interpreting R Charts

346
R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum...
346
Interpreting Run Charts01:25

Interpreting Run Charts

3.1K
Run charts, essentially line graphs plotted over time, serve as fundamental yet effective tools for process analysis. They chronicle data sequentially, facilitating the identification of trends, shifts, or cyclical movements. This graphical representation is instrumental in determining whether a process is stable or exhibits signs of potential instability indicative of special cause variation. In the healthcare domain, run charts depict infection rates over time, enabling hospitals to monitor...
3.1K
Mass Spectrum: Interpretation01:24

Mass Spectrum: Interpretation

2.8K
An unknown compound can be established by identifying the molecular ion peak in the mass spectrum. The molecular ion peak is often weak or absent due to the predominance of fragmentation in high-energy electron beams. In such cases, a soft-energy electron beam can be used to scan the spectrum to enhance the intensity of the molecular ion peak. Additionally, chemical ionization, field ionization, and desorption ionization spectra are used to obtain a relatively intense molecular ion peak.To...
2.8K
Interpretation of Confidence Intervals01:19

Interpretation of Confidence Intervals

9.4K
A confidence interval is a better estimate of the population than a point estimate, as it uses a range of values from a sample instead of a single value.
Confidence intervals have confidence coefficients that are crucial for their interpretation. The most common confidence coefficients are 0.90, 0.95, and 0.99, which can be written as percentages–90%, 95%, and 99%, respectively.
Suppose a person calculates a confidence interval with a confidence coefficient of 0.95. In that case, they can...
9.4K
Interpreting X̄ Charts01:13

Interpreting X̄ Charts

305
Interpreting x̄ charts, a type of control chart used in statistical process control helps monitor the variation in processes over time. The x̄ chart is based on the sample mean and allows for monitoring variations in the process mean over time. These charts are pivotal for quality assurance in manufacturing and other sectors.
An x̄ chart plots the values of individual measurements over time against control limits calculated from historical data. The central line...
305

You might also read

Related Articles

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

Sort by
Same author

AMPK-mediated prevention of vascular dysfunction with metformin: Experimental and population-based evidence.

British journal of pharmacology·2026
Same author

In Defence of Behavioral Genetics.

Twin research and human genetics : the official journal of the International Society for Twin Studies·2026
Same author

Publisher Correction: Multi-ancestry genome-wide association analyses of refractive error augment genetic discovery and polygenic prediction.

Nature genetics·2026
Same author

Author Correction: Genome-wide fine-mapping improves identification of causal variants.

Nature genetics·2026
Same author

<i>Trans</i>-eQTLs reveal the architecture of human gene regulatory networks.

medRxiv : the preprint server for health sciences·2026
Same author

Multi-ancestry genome-wide association analyses of refractive error augment genetic discovery and polygenic prediction.

Nature genetics·2026
Same journal

Inherited long telomeres induce a genome-wide transcriptional response in budding yeast.

Genetics·2026
Same journal

Adaptive Dynamics of Quantitative Traits in a Steadily Changing Environment.

Genetics·2026
Same journal

Functional Landscape of Zebrafish Gonadotropins and Receptors: A Comprehensive Genetic Analysis.

Genetics·2026
Same journal

Synergistic actions of Nup43 and Myosin VI drive actin cone assembly during Drosophila spermiogenesis.

Genetics·2026
Same journal

Identification of two Cryptococcus neoformans heme transporters involved in Fhb1-mediated nitrosative stress protection in a fission yeast model.

Genetics·2026
Same journal

Analysis of a hypomorphic mei-P26 mutation reveals coordination between developmental programming of germ cells and meiotic chromosome dynamics.

Genetics·2026
See all related articles

Related Experiment Video

Updated: Jan 24, 2026

Comprehensive Autopsy Program for Individuals with Multiple Sclerosis
09:41

Comprehensive Autopsy Program for Individuals with Multiple Sclerosis

Published on: July 19, 2019

12.0K

Comprehensive Multiple eQTL Detection and Its Application to GWAS Interpretation.

Biao Zeng1, Luke R Lloyd-Jones2, Grant W Montgomery2

  • 1School of Biological Sciences and Center for Integrative Genomics, Georgia Institute of Technology, Atlanta, Georgia 30332.

Genetics
|May 25, 2019
PubMed
Summary
This summary is machine-generated.

Multiple genetic variants can influence gene expression, challenging the single-variant assumption in expression QTL (eQTL) studies. Our research reveals secondary cis-eQTL signals are common, impacting gene-trait associations.

Keywords:
PolyQTLcolocalizationconditional associationfine mappinggene regulationlinkage disequilibrium

More Related Videos

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
05:01

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

Published on: July 1, 2020

3.7K
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

4.8K

Related Experiment Videos

Last Updated: Jan 24, 2026

Comprehensive Autopsy Program for Individuals with Multiple Sclerosis
09:41

Comprehensive Autopsy Program for Individuals with Multiple Sclerosis

Published on: July 19, 2019

12.0K
A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
05:01

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

Published on: July 1, 2020

3.7K
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

4.8K

Area of Science:

  • Genetics
  • Genomics
  • Molecular Biology

Background:

  • Expression quantitative trait loci (eQTL) analysis links genetic variants to gene expression levels.
  • Current eQTL studies often assume a single causal variant per association, potentially overlooking complex regulatory mechanisms.

Purpose of the Study:

  • To investigate the prevalence and impact of secondary cis-eQTL signals on peripheral blood gene expression.
  • To assess the sharing of cis-eQTL signals across different human cohorts and platforms.
  • To explore the colocalization of eQTLs with genome-wide association study (GWAS) hits for human traits and diseases.

Main Methods:

  • Utilized two large human cohort studies (>2500 samples each) with whole-genome genotypes (CAGE and Framingham Heart Study).
  • Applied stepwise conditional modeling to identify multiple cis-eQTL signals.
  • Performed Bayesian colocalization analysis with the BIOS RNAseq dataset and GWAS data.

Main Results:

  • Approximately 40% of over 3500 eGenes showed evidence of multiple cis-eQTL signals in microarray datasets.
  • Colocalization analysis indicated that 50-60% of primary eQTLs are shared across studies.
  • Colocalization of eQTLs with GWAS hits identified 1349 genes associated with 591 human traits/diseases, with 10-40% potentially involving non-primary cis-eQTLs.

Conclusions:

  • Secondary cis-eQTL signals are prevalent and contribute to the genetic architecture of gene expression.
  • Understanding multi-site regulation of gene expression is crucial for interpreting eQTL-trait associations.
  • Findings provide a resource for exploring gene expression regulation and its link to complex traits and diseases.