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

Applications of Molecular Taxonomy01:20

Applications of Molecular Taxonomy

614
Molecular taxonomy has revolutionized the understanding and classification of bacteria, providing precise insights into their diversity, evolutionary relationships, and ecological roles. By utilizing molecular techniques such as DNA sequencing and fingerprinting, researchers have made significant strides in various fields related to bacterial studies.Resolving Taxonomic AmbiguitiesMolecular taxonomy has been instrumental in distinguishing closely related bacterial species initially thought to...
614
Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

5.2K
The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
5.2K
Pedigree Analysis01:35

Pedigree Analysis

90.1K
Overview
90.1K
Genomics02:02

Genomics

41.0K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
41.0K
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

15.9K
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...
15.9K
Biostatistics: Overview01:20

Biostatistics: Overview

937
Biostatistics plays a crucial role in understanding and analyzing data in healthcare and biology. Biostatisticians conduct experiments, gather evidence, and draw meaningful conclusions using statistical methods and techniques. Different variables form the foundation of biostatistical analysis, allowing researchers to understand and interpret data effectively. These variables are classified into different types, each serving a specific purpose in statistical analysis.
Discrete variables are...
937

You might also read

Related Articles

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

Sort by
Same author

eQTM (expression quantitative trait methylation) Atlas: a comprehensive resource of over 11 million DNA methylation-gene expression associations through across 11 tissues and 4 diseases.

bioRxiv : the preprint server for biology·2026
Same author

Plasma proteomics improves thrombosis prediction in patients with cancer and identifies targetable IL-17-driven endothelial activation.

Science translational medicine·2026
Same author

Cell-type- and state-resolved transcriptomics uncovers distinct T cell and monocyte dysregulation in multiple sclerosis.

Cell reports·2026
Same author

Single-Cell Atlas of Renal Cell Carcinoma Brain Metastasis Uncovers Mechanisms of Immune Dysfunction and Resistance.

bioRxiv : the preprint server for biology·2026
Same author

Decoding spatial transcriptomics across multicellular and subcellular resolutions.

Nature communications·2026
Same author

Semi-parametric empirical bayes method for multiplet detection in snATAC-seq with probabilistic multi-omic integration.

PLoS computational biology·2026
Same journal

Geographic distribution of sex chromosome polymorphism in Anastrepha fraterculus sp. 1 from Argentina.

BMC genetics·2020
Same journal

Development and characterization of a pupal-colour based genetic sexing strain of Anastrepha fraterculus sp. 1 (Diptera: Tephritidae).

BMC genetics·2020
Same journal

Improvement on the genetic engineering of an invasive agricultural pest insect, the cherry vinegar fly, Drosophila suzukii.

BMC genetics·2020
Same journal

Precise single base substitution in the shibire gene by CRISPR/Cas9-mediated homology directed repair in Bactrocera tryoni.

BMC genetics·2020
Same journal

Climate stress resistance in male Queensland fruit fly varies among populations of diverse geographic origins and changes during domestication.

BMC genetics·2020
Same journal

Genetic structure and symbiotic profile of worldwide natural populations of the Mediterranean fruit fly, Ceratitis capitata.

BMC genetics·2020
See all related articles

Related Experiment Video

Updated: Feb 23, 2026

Assisted Selection of Biomarkers by Linear Discriminant Analysis Effect Size LEfSe in Microbiome Data
04:57

Assisted Selection of Biomarkers by Linear Discriminant Analysis Effect Size LEfSe in Microbiome Data

Published on: May 16, 2022

17.6K

LAIT: a local ancestry inference toolkit.

Daniel Hui1, Zhou Fang2, Jerome Lin3

  • 1Department of Computer Science, University of Pittsburgh, Pittsburgh, PA, 15213, USA.

BMC Genetics
|September 8, 2017
PubMed
Summary
This summary is machine-generated.

A new toolkit, Local Ancestry Inference Toolkit (LAIT), simplifies using multiple local ancestry inference software. LAIT enhances convenience for researchers, especially those new to bioinformatics, by standardizing input and output files.

Keywords:
AdmixtureLocal ancestry inference

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

2.8K
A Method for Targeted 16S Sequencing of Human Milk Samples
09:09

A Method for Targeted 16S Sequencing of Human Milk Samples

Published on: March 23, 2018

10.3K

Related Experiment Videos

Last Updated: Feb 23, 2026

Assisted Selection of Biomarkers by Linear Discriminant Analysis Effect Size LEfSe in Microbiome Data
04:57

Assisted Selection of Biomarkers by Linear Discriminant Analysis Effect Size LEfSe in Microbiome Data

Published on: May 16, 2022

17.6K
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

2.8K
A Method for Targeted 16S Sequencing of Human Milk Samples
09:09

A Method for Targeted 16S Sequencing of Human Milk Samples

Published on: March 23, 2018

10.3K

Area of Science:

  • Genetics
  • Bioinformatics
  • Population Genetics

Background:

  • Local ancestry inference is crucial for identifying disease-susceptible loci in admixed populations.
  • Existing software for local ancestry inference often requires specific input/output formats, causing practical difficulties.
  • Admixed individuals present unique challenges and opportunities in genetic research.

Purpose of the Study:

  • To develop a user-friendly toolkit (LAIT) for local ancestry inference.
  • To streamline the process of using multiple local ancestry inference software packages.
  • To standardize input and output for popular local ancestry inference tools.

Main Methods:

  • Developed the Local Ancestry Inference Toolkit (LAIT).
  • LAIT converts standardized files to software-specific formats for HAPMIX, LAMP, LAMP-LD, and ELAI.
  • Tested LAIT with simulated and real data, evaluating accuracy and computational resources.

Main Results:

  • LAIT successfully standardizes input and output for four popular local ancestry inference software.
  • Demonstrated LAIT's convenience in running multiple local ancestry inference tools.
  • Evaluated the performance, accuracy, and resource usage of supported software packages.

Conclusions:

  • LAIT facilitates the use of local ancestry inference software.
  • The toolkit is particularly beneficial for users with limited bioinformatics experience.
  • LAIT enhances accessibility and efficiency in local ancestry inference research.