Jove
Visualize
Contact Us

Related Concept Videos

Incomplete Dominance01:43

Incomplete Dominance

32.4K
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.
32.4K
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

16.6K
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...
16.6K
Genomic Imprinting and Inheritance02:30

Genomic Imprinting and Inheritance

38.7K
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...
38.7K
Human Genetics01:28

Human Genetics

1.9K
Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
The complex relationship between genetics and psychology is observable through common biological components such...
1.9K
Genomics02:02

Genomics

41.7K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
41.7K
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

19.8K
A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
19.8K

You might also read

Related Articles

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

Sort by
Same author

Modeling the length distribution of gene conversion tracts in humans from the UK Biobank sequence data.

PLoS genetics·2025
Same author

Multiple-testing corrections in selection scans using identity-by-descent segments.

American journal of human genetics·2025
Same author

Estimating gene conversion rates from population data using multi-individual identity by descent.

American journal of human genetics·2025
Same author

Identity-By-Descent Mapping Using Multi-Individual IBD With Genome-Wide Multiple Testing Adjustment.

Genetic epidemiology·2025
Same author

Fast simulation of identity-by-descent segments.

Bulletin of mathematical biology·2025
Same author

Estimating gene conversion rates from population data using multi-individual identity by descent.

bioRxiv : the preprint server for biology·2025
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 Experiment Video

Updated: Mar 27, 2026

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

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

40.1K

Genotype Imputation with Millions of Reference Samples.

Brian L Browning1, Sharon R Browning2

  • 1Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA 98195, USA; Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.

American Journal of Human Genetics
|January 11, 2016
PubMed
Summary
This summary is machine-generated.

Beagle v.4.1 offers a scalable genotype imputation method for large reference panels. This efficient tool achieves high accuracy and speed, outperforming existing methods for genomic data analysis.

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

10.8K
Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
09:34

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

35.0K

Related Experiment Videos

Last Updated: Mar 27, 2026

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

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

40.1K
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

10.8K
Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
09:34

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

35.0K

Area of Science:

  • Genomics
  • Computational Biology
  • Bioinformatics

Background:

  • Genotype imputation is crucial for analyzing large-scale genomic datasets.
  • Existing imputation methods face challenges with scalability and computational efficiency when handling millions of reference samples.

Purpose of the Study:

  • To introduce Beagle v.4.1, a novel genotype imputation method designed for scalability.
  • To evaluate the performance of Beagle v.4.1 in terms of accuracy, speed, and memory efficiency compared to existing tools.

Main Methods:

  • The study utilizes the Li and Stephens model, implemented in Beagle v.4.1, featuring parallelization and memory efficiency.
  • The method restricts the probability model to genotyped markers and employs linear interpolation for imputing ungenotyped variants.
  • Performance comparisons were conducted using data from the 1000 Genomes Project, UK10K Project, and simulated datasets.

Main Results:

  • Beagle v.4.1 demonstrates comparable accuracy to Impute2 and Minimac3.
  • Beagle v.4.1 exhibits significantly higher throughput and lower memory consumption, especially with large reference panels.
  • Compared to Impute2, Beagle's throughput was over 100x greater for 50,000 reference samples.
  • Minimac3 consumed 26x more memory and 15x more CPU time than Beagle for 200,000 reference samples.

Conclusions:

  • Beagle v.4.1 is a highly scalable and efficient genotype imputation method suitable for millions of reference samples.
  • The method offers a practical solution for large-scale genomic studies requiring fast and accurate genotype imputation.
  • Beagle v.4.1 represents a significant advancement in computational genomics, enabling deeper insights from massive datasets.