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Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

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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,...
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Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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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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Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

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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%...
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Principles of Pharmacogenetics: Types of Genetic Variants01:27

Principles of Pharmacogenetics: Types of Genetic Variants

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The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...
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Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

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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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Sanger Sequencing01:57

Sanger Sequencing

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DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
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Related Experiment Video

Updated: May 1, 2026

A Method to Study the C924T Polymorphism of the Thromboxane A2 Receptor Gene
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A Method to Study the C924T Polymorphism of the Thromboxane A2 Receptor Gene

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Single nucleotide polymorphism (SNP)-strings: an alternative method for assessing genetic associations.

Douglas S Goodin1, Pouya Khankhanian1

  • 1Department of Neurology, University of California San Francisco, San Francisco, California, United States of America; UCSF Multiple Sclerosis Center, University of California San Francisco, San Francisco, California, United States of America.

Plos One
|April 15, 2014
PubMed
Summary

This study introduces a novel SNP-string method for accurate haplotype identification, improving genome-wide association study (GWAS) power. The method enhances the detection of genetic associations by precisely identifying disease-associated single nucleotide polymorphisms (SNPs).

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Area of Science:

  • Genetics and Genomics
  • Statistical Genetics
  • Bioinformatics

Background:

  • Genome-wide association studies (GWAS) identify disease associations with single nucleotide polymorphisms (SNPs) across genomic locations.
  • SNPs can exist on multiple SNP-haplotypes, potentially diluting the observed disease association and lowering the odds ratio.

Purpose of the Study:

  • To develop a method for accurately identifying the two SNP-haplotypes that form an individual's SNP-genotype.
  • To improve the detection of genetic associations and enhance the power of GWAS.

Main Methods:

  • Developed a probabilistic method to define and resolve 'SNP-strings' representing haplotypes from eleven adjacent SNPs across ∼200 kb.
  • Modeled two multiple sclerosis (MS)-associated genetic regions: DRB1 and MMEL1.
  • Compared the SNP-string method to the SHAPEIT-2 phasing algorithm, evaluating concordance across different genomic windows.

Main Results:

  • The SNP-string method identified a small number of prevalent SNP-strings in the modeled regions.
  • SHAPEIT-2 showed inaccuracies with a 200 kb window but achieved over 99% concordance with the SNP-string method when the window was increased to 2,000 kb.
  • The SNP-string method demonstrated higher accuracy and consistency across the entire region compared to SHAPEIT-2, especially in areas of lower concordance.

Conclusions:

  • Accurate haplotype identification is crucial for enhancing the detection of genetic associations in GWAS.
  • The SNP-string method offers a straightforward approach to improve haplotype resolution.
  • This method can be extended to larger genomic regions, boosting GWAS power and potentially re-analyzing previous studies.