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Related Concept Videos

Human Genetics01:28

Human Genetics

Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
The complex relationship between genetics and psychology is observable through common biological components such...
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...
Incomplete Dominance01:43

Incomplete Dominance

Gregor Mendel's work (1822 - 1884) was primarily focused on pea plants. Through his initial experiments, he determined that every gene in a diploid cell has two variants called alleles inherited from each parent. He suggested that amongst these two alleles, one allele is dominant in character and the other recessive. The combination of alleles determines the phenotype of a gene in an organism.
Genomics02:02

Genomics

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...
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

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,...
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...

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Related Experiment Video

Updated: May 20, 2026

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

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

Genotype Imputation for Latinos Using the HapMap and 1000 Genomes Project Reference Panels.

Xiaoyi Gao1, Talin Haritunians, Paul Marjoram

  • 1Department of Ophthalmology, Keck School of Medicine, University of Southern California Los Angeles, CA, USA.

Frontiers in Genetics
|July 4, 2012
PubMed
Summary

The 1000 Genomes Project reference panel, specifically AMR+CEU+YRI, offers the highest genotype imputation accuracy for Latino populations in genome-wide association studies. Including Asian samples may decrease accuracy.

Keywords:
1000 Genomes ProjectHapMap ProjectLatinogenotype imputation

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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Area of Science:

  • Genetics
  • Genomics
  • Population Genetics

Background:

  • Genotype imputation is crucial for genome-wide association studies (GWAS) and meta-analyses, enhancing genomic coverage and data pooling across different genotyping platforms.
  • Current genotype imputation resources for Latino populations are limited compared to European ancestry groups due to a lack of adequate reference data.
  • The 1000 Genomes Project is increasingly used for reference panels, but its utility for Latino imputation requires detailed evaluation.

Purpose of the Study:

  • To evaluate the accuracy of genotype imputation in Latino populations using public reference panels.
  • To identify the optimal reference panel for genotype imputation in Latinos for genome-wide association studies.
  • To provide a guide for future imputation-based analyses in Latino populations.

Main Methods:

  • Utilized simulation studies with Illumina OmniExpress GWAS data from the Los Angeles Latino Eye Study.
  • Employed the MACH software package for genotype imputation.
  • Evaluated imputation accuracy using the 1000 Genomes Project reference panels, including variations with and without Asian samples.

Main Results:

  • The 1000 Genomes Project reference panel comprising African, European, and Yoruba populations (AMR+CEU+YRI) demonstrated the highest imputation accuracy for Latinos.
  • Inclusion of Asian samples in the reference panel was found to potentially reduce imputation accuracy for Latino populations.
  • Imputation accuracy was detailed for each autosomal chromosome using the 1000 Genomes Project panel for Latinos.

Conclusions:

  • The AMR+CEU+YRI panel from the 1000 Genomes Project is recommended for optimal genotype imputation accuracy in Latino populations.
  • Researchers should carefully consider the composition of reference panels to maximize imputation accuracy in diverse populations.
  • This study provides essential data to guide future genome-wide association studies and meta-analyses targeting Latino individuals.