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

What is Population Genetics?01:25

What is Population Genetics?

A population is composed of members of the same species that simultaneously live and interact in the same area. When individuals in a population breed, they pass down their genes to their offspring. Many of these genes are polymorphic, meaning that they occur in multiple variants. Such variations of a gene are referred to as alleles. The collective set of all the alleles within a population is known as the gene pool.While some alleles of a given gene might be observed commonly, other variants...
Pedigree Analysis01:35

Pedigree Analysis

Overview
Pedigree Analysis01:35

Pedigree Analysis

Overview
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...
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...
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...

You might also read

Related Articles

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

Sort by
Same author

ANPELA: analysis and performance assessment of the label-free quantification workflow for metaproteomic studies.

Briefings in bioinformatics·2019
Same author

The Effects of Warfarin on the Pharmacokinetics of Senkyunolide I in a Rat Model of Biliary Drainage After Administration of Chuanxiong.

Frontiers in pharmacology·2019
Same author

Biomarker Discovery for Immunotherapy of Pituitary Adenomas: Enhanced Robustness and Prediction Ability by Modern Computational Tools.

International journal of molecular sciences·2019
Same author

5-Aminothiophene-2,4-dicarboxamide analogues as hepatitis B virus capsid assembly effectors.

European journal of medicinal chemistry·2018
Same author

Novel Hepatitis B Virus Capsid-Targeting Antiviral That Aggregates Core Particles and Inhibits Nuclear Entry of Viral Cores.

ACS infectious diseases·2018
Same author

Gene expression profiling reveals differential patterns between microcystic congenital cystic adenomatoid malformation and congenital lobar emphysema.

Early human development·2018

Related Experiment Video

Updated: Jun 27, 2026

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations.

Jukka Corander1, Pekka Marttinen, Jukka Sirén

  • 1Department of Mathematics, Fänriksgatan 3B, Abo Akademi University, Abo, Finland. jukka.corander@abo.fi

BMC Bioinformatics
|December 18, 2008
PubMed
Summary
This summary is machine-generated.

This study enhances Bayesian methods for population genetics, offering new tools in BAPS software to analyze complex genetic structure in large datasets. These advanced statistical approaches improve genetic inference and handle increasing molecular data challenges.

More Related Videos

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

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

Published on: December 7, 2021

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Related Experiment Videos

Last Updated: Jun 27, 2026

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

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

Published on: December 7, 2021

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Area of Science:

  • Population genetics
  • Statistical modeling
  • Bioinformatics

Background:

  • Numerous Bayesian statistical models and software for population genetic structure analysis exist.
  • Current methods, while useful, may be insufficient for increasingly complex biological problems and large molecular datasets.
  • Previous work introduced the Bayesian Analysis of Population Structure (BAPS) software.

Purpose of the Study:

  • To enhance statistical approaches for analyzing the growing volume of molecular data in population genetics.
  • To introduce new statistical tools within the BAPS software to address limitations of existing methods.
  • To improve the analysis of genetic structure and admixture in populations.

Main Methods:

  • Development and implementation of new Bayesian statistical models in BAPS software.
  • Genetic mixture modeling with user-specified cluster numbers.
  • Estimation of admixture levels using a genetic linkage model.
  • Tracking alleles of different ancestry.
  • Comparison of a priori hypotheses using Bayes' theorem.
  • Improvements in computational efficiency for large datasets, including parallel processing capabilities.

Main Results:

  • Introduction of enhanced statistical tools in the latest BAPS version.
  • Capability to fit genetic mixture models and estimate admixture levels.
  • Identification of individual alleles representing different ancestries.
  • Direct comparison of population structure hypotheses.
  • Improved computational performance for analyzing large and complex genetic datasets.
  • Facilitation of distributed computing for single dataset analysis.

Conclusions:

  • The new Bayesian modeling methods in BAPS provide enhanced tools for understanding population genetic structure.
  • Implementations in BAPS are designed to meet the demands of large-scale population genetics data analysis.
  • The BAPS software is freely available for major operating systems.