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

Evolutionary Relationships through Genome Comparisons

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

You might also read

Related Articles

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

Sort by

Same author

Fine-Mapping of HLA Effects in Oral and Non-Oral Lichen Planus.

HLA·2026

Same author

Comparing Pathway-Informed Polygenic Risk Score Strategies: A multi-cohort evaluation of Amyloid-β.

medRxiv : the preprint server for health sciences·2026

Same author

AdaptMol: domain adaptation for molecular image recognition with limited supervision.

Journal of cheminformatics·2026

Same author

The state of standardized musculoskeletal terminology for healthcare reuse:A scoping review.

International journal of medical informatics·2026

Same author

Sex and APOE ε4 genotype modify risk factor associations with cerebral amyloid angiopathy: a multi-cohort autopsy study.

Alzheimer's research & therapy·2026

Same author

A comprehensive systematic review dataset is a rich resource for training and evaluation of AI systems for title and abstract screening.

Research synthesis methods·2026

Search research articles

Related Experiment Video

Updated: Nov 28, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Evaluation of consensus strategies for haplotype phasing.

Ziad Al Bkhetan¹, Gursharan Chana², Kotagiri Ramamohanarao³

¹School of Computing and Information Systems at the University of Melbourne.

Briefings in Bioinformatics

|November 25, 2020

Summary

Combining multiple haplotype phasing estimates improves accuracy. A consensus approach using multiple tools reduces errors by 10% and enhances downstream genotype imputation, offering a robust strategy for genetic analyses.

Keywords:

consensus estimator genotype imputation haplotype phasing

More Related Videos

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Methods to Increase the Sensitivity of High Resolution Melting Single Nucleotide Polymorphism Genotyping in Malaria

Methods to Increase the Sensitivity of High Resolution Melting Single Nucleotide Polymorphism Genotyping in Malaria

Published on: November 10, 2015

Related Experiment Videos

Last Updated: Nov 28, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Methods to Increase the Sensitivity of High Resolution Melting Single Nucleotide Polymorphism Genotyping in Malaria

Methods to Increase the Sensitivity of High Resolution Melting Single Nucleotide Polymorphism Genotyping in Malaria

Published on: November 10, 2015

Area of Science:

Genetics
Bioinformatics
Computational Biology

Background:

Haplotype phasing is crucial for genetic studies, but inaccurate phasing can lead to errors in downstream analyses.
Combining multiple phasing estimates is a proposed method to enhance accuracy, yet it requires thorough investigation.

Purpose of the Study:

To comprehensively evaluate consensus strategies for improving haplotype phasing accuracy.
To assess the impact of different consensus paradigms and constituent tools on phasing performance across diverse datasets.
To determine the effect of consensus phasing on the downstream task of genotype imputation.

Main Methods:

Developed two consensus strategies: voting across outputs from multiple phasing tools and using multiple outputs from a single non-deterministic tool.
Evaluated performance across datasets with varying characteristics (population, sample size, variant density/frequency).
Assessed the impact on genotype imputation accuracy using Minimac3, pbwt, and BEAGLE5.

Main Results:

Consensus phasing from multiple tools reduced phasing errors by an average of 10% in European populations compared to individual tools.
The consensus approach demonstrated the highest accuracy across diverse populations, sample sizes, and variant characteristics.
Consensus phasing significantly improved genotype imputation accuracy with widely used tools.

Conclusions:

A consensus strategy, particularly using multiple tools, is a highly effective method for accurate haplotype phasing.
This approach enhances downstream genotype imputation and provides valuable guidance for genetic analyses.
The consHap implementation offers a freely available tool for consensus haplotype phasing.