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Related Concept Videos

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,...
Sampling Plans01:23

Sampling Plans

Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
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%...
Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

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...
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Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
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Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures from...

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Updated: Jun 25, 2026

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

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

SNP selection and multidimensional scaling to quantify population structure.

Kelci Miclaus1, Russ Wolfinger, Wendy Czika

  • 1Department of Statistics, North Carolina State University, Raleigh, North Carolina, USA. Kelci.Miclaus@jmp.com

Genetic Epidemiology
|February 6, 2009
PubMed
Summary
This summary is machine-generated.

Population stratification in Genome Wide Association Studies (GWAS) can be visualized and quantified using Hardy-Weinberg disequilibrium (HWD) and non-metric multidimensional scaling (MDS). This method effectively identifies informative single nucleotide polymorphisms (SNPs) for association studies.

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

  • Population Genetics
  • Statistical Genomics
  • Bioinformatics

Background:

  • Population stratification is a critical confounding factor in large-scale Genome Wide Association Studies (GWAS).
  • Accurate visualization and quantification methods are essential for controlling population structure effects in genetic association studies.

Purpose of the Study:

  • To develop and validate a methodology for selecting single nucleotide polymorphisms (SNPs) informative for population stratification.
  • To introduce a visualization technique for population substructure using non-metric multidimensional scaling (MDS).

Main Methods:

  • SNP selection based on deviation from Hardy-Weinberg equilibrium (HWE), specifically Hardy-Weinberg disequilibrium (HWD).
  • Application of non-metric multidimensional scaling (MDS), a distance-based multivariate technique, for population stratification visualization.
  • Validation through simulations and empirical analysis using HapMap samples.

Main Results:

  • SNP selection using HWD is robust against confounding linkage disequilibrium (LD) patterns, unlike previous methods.
  • Non-metric MDS is demonstrated as a preferable visualization tool compared to principal components for HWD-selected SNPs.
  • The proposed method effectively differentiates population substructure.

Conclusions:

  • The developed methodology provides a simple and effective approach for selecting substructure-informative markers.
  • This tool aids in exploring the impact of population stratification in genetic association studies.
  • The combination of HWD and MDS offers a powerful strategy for managing population structure in GWAS.