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

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%...
Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This number is...

You might also read

Related Articles

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

Sort by
Same author

Non-Parametric Ancestry Adjustment for Polygenic Scores.

medRxiv : the preprint server for health sciences·2026
Same author

Integrating social determinants of health and genetic risk in disease risk models.

American journal of human genetics·2026
Same author

Revisiting Founder Populations in an Age of Global Biobanks.

Annual review of genomics and human genetics·2026
Same author

Analytic Choices Shape Genomic Risk Estimates from Electronic Health Records: Coronary Heart Disease in eMERGE IV.

medRxiv : the preprint server for health sciences·2026
Same author

The landscape of genomic and socioeconomic variables in colorectal cancer patients based on genetic ancestry.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology·2026
Same author

Determinants of DNA-sequence-based Diagnostic Yield in the CSER Consortium.

medRxiv : the preprint server for health sciences·2026

Related Experiment Video

Updated: May 13, 2026

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution
13:47

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Published on: February 25, 2015

26.2K

GBStools: A Statistical Method for Estimating Allelic Dropout in Reduced Representation Sequencing Data.

Thomas F Cooke1, Muh-Ching Yee2, Marina Muzzio1,3,4

  • 1Department of Genetics, Stanford University, Stanford, California, United States of America.

Plos Genetics
|February 2, 2016
PubMed
Summary
This summary is machine-generated.

Genotyping-by-sequencing (GBS) errors from restriction site variation can be corrected using the new GBStools software. This improves genetic variation accuracy, especially for large datasets and diverse species.

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 4, 2018

12.6K
Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2
10:10

Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2

Published on: September 19, 2021

41.0K

Related Experiment Videos

Last Updated: May 13, 2026

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution
13:47

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Published on: February 25, 2015

26.2K
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 4, 2018

12.6K
Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2
10:10

Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2

Published on: September 19, 2021

41.0K

Area of Science:

  • Genomics
  • Population Genetics
  • Bioinformatics

Background:

  • Reduced representation sequencing, like genotyping-by-sequencing (GBS), offers cost-effective genetic variation analysis without a reference genome.
  • GBS is valuable for non-model organisms in genetic mapping and population studies.
  • Higher variant calling error rates in GBS, particularly from restriction site polymorphisms, limit its application.

Purpose of the Study:

  • To develop and evaluate a statistical method and software (GBStools) for correcting genotype errors in GBS data caused by restriction site polymorphisms.

Main Methods:

  • Developed a statistical method implemented in the GBStools software package.
  • Evaluated GBStools using simulated datasets with varying sample sizes, coverage, and mutation rates.
  • Tested GBStools on empirical human datasets (N=8 and N=63) and for human population genetic inference.

Main Results:

  • GBStools significantly improved genotype accuracy compared to standard filters like Hardy-Weinberg equilibrium p-values in simulations.
  • The software is most effective for datasets with over 100 samples and 40X coverage, with greater benefits in species with high genomic diversity.
  • Applied to Argentine human populations, GBS and GBStools revealed diverse ancestry proportions and an excess of singletons, suggesting recent population growth.

Conclusions:

  • GBStools provides an effective computational solution for mitigating restriction site polymorphism errors in GBS data.
  • The method enhances the reliability of GBS for genetic mapping and population genetics, particularly in diverse species and large cohorts.
  • GBStools facilitates robust population genetic inference, aiding in the understanding of demographic histories.