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Single Nucleotide Polymorphisms-SNPs

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,...

Comparing Copy Number Variations and SNPs

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%...

Genome-wide Association Studies-GWAS

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...

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Related Experiment Video

Updated: Jun 18, 2026

Infinium Assay for Large-scale SNP Genotyping Applications

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

SNPs for a universal individual identification panel.

Andrew J Pakstis¹, William C Speed, Rixun Fang

¹Department of Genetics, Yale University School of Medicine, 333 Cedar Street, 208005, New Haven, CT 06520, USA.

|November 26, 2009

Summary

This summary is machine-generated.

We developed 92 globally applicable SNPs for individual identification (IISNPs) with extremely low genotype match probabilities. This universally applicable panel enhances forensic science and genetic studies across diverse populations.

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

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Published on: June 21, 2018

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Last Updated: Jun 18, 2026

Infinium Assay for Large-scale SNP Genotyping Applications

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

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

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

Published on: June 21, 2018

Area of Science:

Genetics
Forensic Science
Population Genetics

Background:

Accurate individual identification is crucial for quality control, sample tracking in large genetic studies, and forensic applications.
Single Nucleotide Polymorphisms (SNPs) are highly effective genetic markers for individual identification.
Existing SNP panels may lack universal applicability across diverse global populations.

Purpose of the Study:

To develop a globally applicable resource of 92 SNPs for highly accurate individual identification (IISNPs).
To ensure the developed SNP panel is effective across diverse ethnic and ancestral groups.
To provide a superior tool for forensic identification, paternity testing, and genetic relationship analysis.

Main Methods:

Screened over 500 candidate SNPs across 44 diverse global populations.
Evaluated SNPs for heterozygosity, F(st) values, and linkage disequilibrium (LD).
Selected 92 IISNPs with high heterozygosity and low F(st) values, ensuring minimal LD for most pairings.

Main Results:

Developed a panel of 92 IISNPs with average heterozygosity >0.4 and F(st) <0.06 across 44 populations.
Identified 86 IISNPs with no significant LD for most pairings, enabling highly accurate identification (probabilities <10^-31).
A subset of 45 unlinked IISNPs provides genotype probabilities <10^-15, suitable for forensic and relationship testing.

Conclusions:

The 92 IISNPs offer a universally applicable and highly discriminating resource for individual identification.
The panel demonstrates superior performance compared to existing forensic markers and previous SNP sets.
This resource significantly advances capabilities in forensics, genetic research, and personal identification globally.