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
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

55
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
55

You might also read

Related Articles

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

Sort by
Same author

Comparing Catheters to Fistulas in Older Patients Starting Hemodialysis (ACCESS HD).

Journal of the American Society of Nephrology : JASN·2026
Same author

Multi-ancestry transcriptome-wide association studies uncover insights into breast cancer genetics and biology.

Nature communications·2026
Same author

CellAwareGNN: Single-Cell Enhanced Knowledge Graph Foundation Model for Drug Indication Prediction.

bioRxiv : the preprint server for biology·2026
Same author

Kernel-smoothed permutation for extreme P-value estimation in genetic association studies.

Genetics·2026
Same author

Tissue-specific transfer learning improves functional variant and therapeutic target discoveries in breast and prostate cancer.

PLoS genetics·2026
Same author

Improved polygenic risk prediction models for breast cancer subtypes in women of African ancestry.

Nature genetics·2026
Same journal

Coexistence of piRNA and KZFP defense systems: Evolutionary dynamics of layered defense against transposable elements.

Genetics·2026
Same journal

Creation and manipulation of bipartite expression transgenes in C. elegans using phiC31 recombinase.

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
See all related articles

Related Experiment Video

Updated: Jul 4, 2025

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

An expression-directed linear mixed model discovering low-effect genetic variants.

Qing Li1, Jiayi Bian2, Yanzhao Qian2

  • 1Department of Biochemistry & Molecular Biology, University of Calgary, Calgary T2N 1N4, Canada.

Genetics
|February 5, 2024
PubMed
Summary
This summary is machine-generated.

Detecting subtle genetic variants is challenging with moderate sample sizes. Our new expression-directed linear mixed model improves the detection of low-effect variants, advancing precision medicine.

Keywords:
gene expressionhuman diseaseslinear mixed modellow-effect genetic variants

More Related Videos

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.1K
An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
10:17

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

22.9K

Related Experiment Videos

Last Updated: Jul 4, 2025

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
Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.1K
An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
10:17

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

22.9K

Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Detecting low-effect genetic variants is crucial for understanding disease pathology and heritability.
  • Moderate sample sizes limit the discovery of subtle genetic signals.
  • Current methods struggle to effectively estimate the polygenic component in genetic models.

Purpose of the Study:

  • To develop a novel method for detecting low-effect genetic variants using moderate sample sizes.
  • To improve the estimation of heritability by incorporating gene expression relevance.
  • To advance precision medicine through enhanced genetic variant detection.

Main Methods:

  • Utilized informative weights from genetically predicted gene expression models.
  • Developed an expression-directed linear mixed model (EDLMM) to estimate the polygenic term.
  • Incorporated gene expression relevance into the genetic background estimation within the linear mixed model.

Main Results:

  • The expression-directed linear mixed model successfully detected subtle signals of low-effect variants in cohorts of ~5,000 individuals.
  • Demonstrated significant power gain at the low-effect end of the genetic etiology spectrum for both binary (WTCCC) and quantitative (NFBC1966) traits.
  • Substantially improved the estimation of missing heritability by identifying additional low-effect variants.

Conclusions:

  • The expression-directed linear mixed model is effective for discovering low-effect genetic variants with moderate sample sizes.
  • This approach enhances the estimation of heritability and advances the field of precision medicine.
  • Accurate detection of low-effect genetic variants contributes to a better understanding of human diseases.