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

Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

7.1K
When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
7.1K
Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

62.5K
Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.
62.5K
Incomplete Dominance01:43

Incomplete Dominance

19.0K
Gregor Mendel's work (1822 - 1884) was primarily focused on pea plants. Through his initial experiments, he determined that every gene in a diploid cell has two variants called alleles inherited from each parent. He suggested that amongst these two alleles, one allele is dominant in character and the other recessive. The combination of alleles determines the phenotype of a gene in an organism.
19.0K
Genomic Imprinting and Inheritance02:30

Genomic Imprinting and Inheritance

30.2K
Diploid organisms inherit genetic material through chromosomes from both parents. Copies of the same gene are known as alleles. In most cases, both alleles are simultaneously expressed and allow various cellular processes to function optimally. If one of the alleles is missing or mutated, the expression of the other allele can compensate; however, this is not true for all genes.
The expression of some genes depends on which parent passed the gene to the offspring, through a phenomenon known as...
30.2K
Multiple Allele Traits01:49

Multiple Allele Traits

32.7K
The Concept of Multiple Allelism
32.7K
Punnett Squares01:00

Punnett Squares

100.1K
Overview
100.1K

You might also read

Related Articles

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

Sort by
Same author

The Poisson CUSUM Chart for Monitoring Small Counts: Addressing the Estimation Uncertainty.

Biometrical journal. Biometrische Zeitschrift·2026
Same author

Can atrial fibrillation ablation outcomes be properly predicted with electrocardiography and artificial intelligence?

European heart journal. Digital health·2026
Same author

Nodal Heterogeneity can Induce Ghost Triadic Effects in Relational Event Models.

Psychometrika·2026
Same author

Continuous non-invasive electrophysiological monitoring in high-risk pregnancies: study protocol of a cohort intervention random sampling study in a tertiary obstetrical care centre in the Netherlands (NIEM-O study).

BMJ open·2025
Same author

Optimizing clinical scientific research: the cohort intervention random sampling study with historical controls.

Journal of comparative effectiveness research·2025
Same author

Symptom networks of psychotic experiences and functional somatic symptoms in adolescence: A cross-sectional study of two population-based cohorts.

Schizophrenia research·2025

Related Experiment Video

Updated: May 4, 2026

Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

41.3K

Probability genotype imputation method and integrated weighted lasso for QTL identification.

Nino Demetrashvili1, Edwin R Van den Heuvel, Ernst C Wit

  • 1Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, Groningen 9747 AG, The Netherlands. n.demetrashvili@rug.nl.

BMC Genetics
|January 1, 2014
PubMed
Summary

This study introduces a novel two-step method for quantitative trait loci (QTL) mapping that accurately imputes missing genetic markers and identifies causal variants using weighted lasso. The approach improves accuracy and outperforms existing methods for genetic trait analysis.

More Related Videos

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii
11:37

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii

Published on: June 22, 2017

18.6K
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

9.2K

Related Experiment Videos

Last Updated: May 4, 2026

Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

41.3K
QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii
11:37

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii

Published on: June 22, 2017

18.6K
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

9.2K

Area of Science:

  • Genetics
  • Statistical Genetics
  • Bioinformatics

Background:

  • Quantitative Trait Loci (QTL) studies often face challenges with missing marker data and identifying a few causal markers among many.
  • Statistical concepts of sparsity and causal inference are relevant to marker selection in genetic studies.

Purpose of the Study:

  • To develop a robust two-step statistical methodology for QTL mapping with binary genotypes, addressing missing data and marker sparsity.
  • To introduce a novel imputation technique for missing genotypes and integrate it with weighted lasso for sparse phenotype inference.

Main Methods:

  • A novel imputation method was developed to estimate missing genotypes, providing probabilities that act as weights.
  • Weighted lasso regression was employed for sparse phenotype inference, selecting predictive markers.
  • The methodology was tested using extensive simulation studies and applied to an Arabidopsis dataset.

Main Results:

  • The proposed imputation method demonstrated higher accuracy in sensitivity and specificity compared to alternatives.
  • Weighted lasso significantly outperformed multiple regression, traditional lasso, and adaptive lasso.
  • Application to Arabidopsis identified known QTL regions and several novel marker associations, particularly for the germination trait Gmax.

Conclusions:

  • The developed two-step methodology is effective for QTL identification, especially under realistic missing data conditions.
  • The imputation and weighted lasso approach offers improved accuracy and marker selection capabilities for genetic studies.