Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Genome-wide Association Studies-GWAS

Genome-wide Association Studies-GWAS

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...

You might also read

Related Articles

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

Sort by

Same author

Designed diversity: from marker-assisted backcrossing to computationally optimised polygenic introgression.

Trends in plant science·2026

Same author

Ascertainment Bias in Cattle SNP Arrays and Implications for Multibreed Genomic Predictions.

Animal genetics·2026

Same author

Negative Energy Balance in Transition Cows Induces Complex Changes in Lipid Profile of Milk.

Metabolites·2026

Same author

Factors affecting recording methane emission phenotypes of composite and crossbreed beef cattle grazing tropical and subtropical rangelands of Northern Australia.

Journal of animal science·2026

Same author

Advancing rust resistance in elite wheat with haplotype mapping and a novel introgression strategy.

Journal of experimental botany·2026

Same author

A geospatial model of entry pathways of lumpy skin disease virus introduction into Australia.

Scientific reports·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

Same journal

Neural and Genetic Mechanisms Regulating Copulation Latency in Male Drosophila melanogaster.

Genetics·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 31, 2026

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

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

Published on: June 21, 2018

Imputation of missing genotypes from sparse to high density using long-range phasing.

Hans D Daetwyler¹, George R Wiggans, Ben J Hayes

¹Biosciences Research Division, Department of Primary Industries, Bundoora 3083, Australia. hans.daetwyler@dpi.vic.gov.au

|June 28, 2011

Summary

This summary is machine-generated.

ChromoPhase is a new algorithm that accurately phases chromosomes and imputes missing genotypes using related individuals. This method shows promise for improving genomic predictions even with imperfectly imputed data.

More Related Videos

Infinium Assay for Large-scale SNP Genotyping Applications

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

Related Experiment Videos

Last Updated: May 31, 2026

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

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

Published on: June 21, 2018

Infinium Assay for Large-scale SNP Genotyping Applications

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

Area of Science:

Genetics
Bioinformatics
Genomic Data Analysis

Background:

Related individuals share long chromosome segments inherited from common ancestors.
Accurate phasing and imputation of genotypes are crucial for genomic studies.
Existing methods may have limitations in handling large datasets and complex pedigrees.

Purpose of the Study:

To introduce ChromoPhase, a novel algorithm for phasing large chromosomal segments.
To evaluate ChromoPhase's performance in imputing missing genotypes using related individuals.
To assess the impact of genotype imputation on genomic prediction accuracy.

Main Methods:

Developed ChromoPhase, an algorithm utilizing related individuals (surrogate parents/offspring) and genotypic similarity to phase chromosomes.
Employed a pedigree-based approach to identify genomic surrogates and shared segments.
Tested ChromoPhase on simulated populations and a real Holstein cattle dataset for phasing and imputation.

Main Results:

ChromoPhase achieved 99.9% accuracy in phasing loci in simulated data.
Successfully imputed over 87% of missing genotypes in simulated data and 92% in real cattle data.
Genomic prediction accuracy showed only a modest reduction despite imperfectly imputed genotypes.

Conclusions:

ChromoPhase is a feasible and accurate method for imputing missing genotypes and potentially full genome sequences.
The algorithm leverages relatedness to improve genomic data quality.
Imputation using ChromoPhase has minimal impact on the accuracy of genomic evaluations.