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

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...
Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

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.In the early 20th century,...
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

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,...
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...

You might also read

Related Articles

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

Sort by
Same author

KANN: estimation of genetic ancestry profiles by nearest neighbor regression.

Nucleic acids research·2026
Same author

Genome-wide association analyses of autoimmune hypothyroidism reveal autoimmune and thyroid-specific contributions and an inverse relationship with cancer risk.

Nature genetics·2026
Same author

Fine-mapping a genome-wide meta-analysis of 98,374 migraine cases identifies 181 sets of candidate causal variants.

Nature communications·2026
Same author

Estimating quantile treatment effect on the original scale of the outcome variable: a case study of common cold treatments.

Trials·2025
Same author

FINEMAP-miss: fine-mapping genome-wide association studies with missing genotype information.

Bioinformatics (Oxford, England)·2025
Same author

Prediction of Episodic Memory With Multiomics Scores.

Biological psychiatry global open science·2025
Same journal

Cross-Domain Transfer Learning from Peptides to Metabolites Using a Multi-Property Fine-Tuned LLM.

Bioinformatics (Oxford, England)·2026
Same journal

Biomedical Concept Recognition with Error-aware Negative-enhanced Ranking Framework.

Bioinformatics (Oxford, England)·2026
Same journal

TEDLH: Domain HMMs for sensitive detection of remote homologues.

Bioinformatics (Oxford, England)·2026
Same journal

PLNFGL: Joint Estimation of Multi-Condition Gene Networks from Single-cell RNA-seq Data.

Bioinformatics (Oxford, England)·2026
Same journal

MCFST: Spatial domain identification method based on multi-view graph convolutional network and graph fusion network.

Bioinformatics (Oxford, England)·2026
Same journal

SpaBiT: Enhancing Spatial Transcriptomics Resolution via Bidirectional Attention Transformers.

Bioinformatics (Oxford, England)·2026
See all related articles

Related Experiment Video

Updated: Jun 19, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Estimating population haplotype frequencies from pooled SNP data using incomplete database information.

Matti Pirinen1

  • 1Department of Mathematics and Statistics, University of Helsinki, PO Box 68, 00014, Helsinki, Finland. matti.pirinen@iki.fi

Bioinformatics (Oxford, England)
|October 29, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces a Bayesian model to estimate haplotype frequencies from pooled DNA, improving accuracy and reducing costs. The method leverages existing haplotype databases for more detailed genetic variation analysis.

More Related Videos

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Related Experiment Videos

Last Updated: Jun 19, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Area of Science:

  • Genetics
  • Bioinformatics

Background:

  • Haplotype structures provide detailed genetic variation insights compared to single-locus analyses.
  • Databases like HapMap facilitate population-specific haplotype information.
  • Analyzing pooled DNA reduces genotyping costs and study complexity.

Purpose of the Study:

  • To develop a Bayesian model for estimating haplotype frequencies from pooled DNA data.
  • To integrate prior haplotype information from databases into the estimation process.
  • To improve the accuracy of haplotype frequency estimation from large DNA pools.

Main Methods:

  • A Bayesian model incorporating database information and a multinormal approximation.
  • Estimation of unknown haplotype numbers and structures as random variables.
  • Implementation in the Hippo program using reversible-jump Markov chain Monte Carlo.

Main Results:

  • The proposed Bayesian method significantly outperforms existing approaches on real human data.
  • Accurate estimation of haplotype frequencies from pooled allelic observations.
  • Successful integration of prior haplotype knowledge into the model.

Conclusions:

  • The developed Bayesian model offers a powerful tool for haplotype frequency estimation from pooled DNA.
  • This approach enhances the understanding of genetic variation by utilizing population-specific haplotype data.
  • The method provides a cost-effective and accurate alternative for large-scale genetic studies.