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

Evolutionary Relationships through Genome Comparisons02:54

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...
Relationship Growth01:27

Relationship Growth

Interpersonal relationships progress through stages, beginning with awareness and moving toward mutuality, where emotional connections deepen. While many relationships remain at moderate levels of mutuality, deeper connections form through self-disclosure, trust, and interdependence.Self-DisclosureSelf-disclosure involves revealing personal information, starting with surface-level details and gradually progressing to more intimate content. As trust grows, individuals feel more comfortable...
Symbiosis00:58

Symbiosis

Symbiotic relationships are long-term, close interactions between individuals of different species that affect the distribution and abundance of those species. When a relationship is beneficial to both species, this is called mutualism. When the relationship is beneficial to one species but neither beneficial nor harmful to the other species, this is called commensalism. When one organism is harmed to benefit another, the relationship is known as parasitism. These types of relationships often...
Microbial Phylogeny01:28

Microbial Phylogeny

Understanding the evolutionary relationships among microorganisms is fundamental to microbial ecology and taxonomy. Phylogenetic trees are essential tools for inferring these relationships, relying primarily on comparative analyses of molecular sequences such as DNA, RNA, or proteins. In microbial studies, these trees typically depict the evolutionary paths of diverse bacterial and archaeal species by mapping genetic differences accumulated over time.Phylogenetic trees are composed of tips,...
Phylogenetic Trees03:21

Phylogenetic Trees

Phylogenetic trees come in many forms. It matters in which sequence the organisms are arranged from the bottom to the top of the tree, but the branches can rotate at their nodes without altering the information. The lines connecting individual nodes can be straight, angled, or even curved.
Phylogenetic Trees03:21

Phylogenetic Trees

Phylogenetic trees come in many forms. It matters in which sequence the organisms are arranged from the bottom to the top of the tree, but the branches can rotate at their nodes without altering the information. The lines connecting individual nodes can be straight, angled, or even curved.

You might also read

Related Articles

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

Sort by
Same author

Multi-omics Biomarker Pipeline Reveals Elevated Levels of Protein-glutamine Gamma-glutamyltransferase 4 in Seminal Plasma of Prostate Cancer Patients.

Molecular & cellular proteomics : MCP·2019
Same author

Fast and Accurate Shared Segment Detection and Relatedness Estimation in Un-phased Genetic Data via TRUFFLE.

American journal of human genetics·2019
Same author

sim1000G: a user-friendly genetic variant simulator in R for unrelated individuals and family-based designs.

BMC bioinformatics·2019
Same author

Identifying Cryptic Relationships.

Methods in molecular biology (Clifton, N.J.)·2017
Same author

Stable Isotope Labeling with Amino Acids (SILAC)-Based Proteomics of Primary Human Kidney Cells Reveals a Novel Link between Male Sex Hormones and Impaired Energy Metabolism in Diabetic Kidney Disease.

Molecular & cellular proteomics : MCP·2017
Same author

Quantification of angiotensin II-regulated proteins in urine of patients with polycystic and other chronic kidney diseases by selected reaction monitoring.

Clinical proteomics·2016
Same journal

Isolation of Mesenchymal Stem Cell-Derived Extracellular Vesicles.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Modeling Melanoma Immune Surveillance by CAR-T Cells in Human Skin Organoids.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Stepwise Optimization of a Matrigel-Based In Vitro Angiogenesis Assay for Reproducible and Quantifiable 2D-Tube Formation Using HUVECs.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Quantifying Mechanical Properties of Fresh Ovarian Tissue with Optical Brillouin Microscopy.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

3D Chromatin Architecture During Early Development: New Methods and New Findings.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Metabolic Plasticity in Embryogenesis Throughout the Lens of NAD<sup></sup>.

Methods in molecular biology (Clifton, N.J.)·2026
See all related articles

Related Experiment Video

Updated: May 25, 2026

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
11:09

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans

Published on: July 17, 2021

Identifying cryptic relationships.

Lei Sun1, Apostolos Dimitromanolakis

  • 1Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada. sun@utstat.toronto.edu

Methods in Molecular Biology (Clifton, N.J.)
|February 7, 2012
PubMed
Summary
This summary is machine-generated.

Detecting and correcting cryptic relatedness in genome-wide association studies (GWAS) is crucial. This study presents two effective methods using PREST and PLINK to address this issue in SNP data from GWAS and NGS.

More Related Videos

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles
10:23

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

Published on: July 11, 2025

Generating Strictly Controlled Stimuli for Figure Recognition Experiments
05:39

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Published on: March 18, 2019

Related Experiment Videos

Last Updated: May 25, 2026

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
11:09

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans

Published on: July 17, 2021

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles
10:23

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

Published on: July 11, 2025

Generating Strictly Controlled Stimuli for Figure Recognition Experiments
05:39

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Published on: March 18, 2019

Area of Science:

  • Genetics
  • Bioinformatics
  • Population Genetics

Background:

  • Cryptic relatedness, including close relatives, is frequently observed in population samples used in genome-wide association studies (GWAS).
  • This relatedness can inflate type 1 error rates and introduce bias in population stratification analyses, such as principal component analysis.
  • Accurate genetic relationship assessment is vital for reliable GWAS results.

Purpose of the Study:

  • To present and detail two effective computational methods for detecting and correcting cryptic relatedness in genetic datasets.
  • To demonstrate the application of these methods using real-world genetic data.

Main Methods:

  • Utilizing high-throughput SNP data from genome-wide association studies (GWAS) and next-generation sequencing (NGS) experiments.
  • Implementing and comparing two established software tools, PREST and PLINK, for cryptic relatedness analysis.
  • Applying analytical and practical strategies to identify and adjust for cryptic relatedness.

Main Results:

  • Successfully detected cryptic relatedness within sample datasets.
  • Demonstrated the effectiveness of PREST and PLINK in identifying close genetic relationships.
  • Provided practical guidance and examples for correcting cryptic relatedness in GWAS data.

Conclusions:

  • Cryptic relatedness is a significant confounder in GWAS that requires careful management.
  • The PREST and PLINK software provide robust and accessible solutions for addressing cryptic relatedness.
  • Implementing these methods enhances the accuracy and reliability of genetic association findings.