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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,...
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%...

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A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes
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SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap.

Andrew D Johnson1, Robert E Handsaker, Sara L Pulit

  • 1The Framingham Heart Study of the National Heart, Lung, and Blood Institute of the National Institutes of Health, USA.

Bioinformatics (Oxford, England)
|November 1, 2008
PubMed
Summary
This summary is machine-generated.

Interpreting genome-wide association studies is challenging due to linkage disequilibrium. The SNAP tool helps identify and annotate proxy single nucleotide polymorphisms (SNPs) to improve study interpretation and fine-mapping experiment design.

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Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Genome-wide association studies (GWAS) are powerful for identifying genetic variants associated with diseases.
  • Interpreting GWAS results can be complex due to linkage disequilibrium (LD), where alleles are inherited together.

Purpose of the Study:

  • To develop a bioinformatics tool to aid in the interpretation of GWAS results.
  • To identify and annotate single nucleotide polymorphisms (SNPs) in linkage disequilibrium (LD) with associated variants.

Main Methods:

  • Development of the SNAP (SNP Annotation and Proxy Search) server.
  • Utilizing HapMap data to identify proxy SNPs.
  • Incorporating functionality for generating graphical plots of LD data.

Main Results:

  • The SNAP server provides a flexible query tool for SNPs.
  • It identifies and annotates nearby SNPs in linkage disequilibrium (LD) based on HapMap data.
  • Graphical plots facilitate visualization of LD relationships.

Conclusions:

  • The SNAP server simplifies the interpretation of GWAS findings.
  • It aids in comparing results across different studies.
  • Facilitates the design of fine-mapping experiments by defining genomic regions with associated variants and their proxies.