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

Next-generation Sequencing03:00

Next-generation Sequencing

100.7K
The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
100.7K
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

19.6K
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,...
19.6K
Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

819
Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
819

You might also read

Related Articles

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

Sort by
Same author

Minocycline-containing therapy in <i>Helicobacter pylori</i> infection: a systematic review and meta-analysis.

Therapeutic advances in gastroenterology·2026
Same author

Inflammasomes in digestive diseases: mechanisms and therapeutic potential.

Molecular biology reports·2026
Same author

Protocol for longitudinal two-photon calcium imaging and holographic optogenetic manipulation to investigate memory in mice.

STAR protocols·2026
Same author

Corrigendum to "Effects of abamectin sublethal doses on the invasive pest Tuta absoluta: Integration of population parameters and transcriptome analysis" [Pesticide Biochemistry and Physiology 218 (2026) 106924].

Pesticide biochemistry and physiology·2026
Same author

Red yeast rice extract's impact on liver health: a pharmacological and metabolomic exploration.

Frontiers in nutrition·2026
Same author

Tumour necrosis factor receptor-associated factor 7 drives leukaemogenesis through the TWIST1-P2RX1-Ca<sup>2+</sup> axis in a mouse model of acute myeloid leukaemia.

Journal of translational medicine·2026

Related Experiment Video

Updated: Mar 18, 2026

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

An empirical Bayes method for genotyping and SNP detection using multi-sample next-generation sequencing data.

Gongyi Huang1, Shaoli Wang2, Xueqin Wang3

  • 1School of Mathematics, Sun Yat-sen University, Guangzhou 510275, China.

Bioinformatics (Oxford, England)
|July 6, 2016
PubMed
Summary

This study introduces a new statistical model for SNP detection using next-generation sequencing data. The empirical Bayes method improves genotyping accuracy and controls false discovery rates for rare variant detection.

More Related Videos

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

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

40.0K
Targeted DNA Methylation Analysis by Next-generation Sequencing
08:38

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

38.2K

Related Experiment Videos

Last Updated: Mar 18, 2026

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

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

40.0K
Targeted DNA Methylation Analysis by Next-generation Sequencing
08:38

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

38.2K

Area of Science:

  • Genomics
  • Bioinformatics
  • Statistical Genetics

Background:

  • Next-generation sequencing (NGS) enables efficient rare variant detection.
  • Accurate quantification of sequencing error rates is crucial for genetic variation identification.
  • Empirical Bayes methods are widely used for estimating sequencing error rates in SNP detection due to their flexibility.

Purpose of the Study:

  • To develop a novel statistical model for analyzing non-reference allele frequency data in NGS.
  • To apply the empirical Bayes method for improved genotyping and SNP detection.
  • To implement an Expectation-Conditional Maximization (ECM) algorithm for parameter estimation.

Main Methods:

  • A novel statistical model was developed to fit non-reference allele frequency data.
  • The empirical Bayes method was utilized for genotyping and SNP detection.
  • An ECM algorithm was implemented for parameter estimation within the statistical model.

Main Results:

  • The proposed method demonstrated a reduction in genotype-call errors compared to existing approaches.
  • High detection power for SNPs was achieved.
  • False Discovery Rate (FDR) was effectively controlled using parameter estimates from the ECM algorithm.

Conclusions:

  • The developed statistical model and empirical Bayes approach enhance SNP detection accuracy in NGS data.
  • The ebGenotyping R package provides a practical implementation of the proposed algorithm.
  • The method offers a robust solution for rare variant detection with controlled error rates.