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Related Concept Videos

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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Single Nucleotide Polymorphisms-SNPs01:05

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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

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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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Related Experiment Video

Updated: Aug 29, 2025

Infinium Assay for Large-scale SNP Genotyping Applications
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SNPMap-An integrated visual SNP interpretation tool.

Miaosen Liu1, Jian Yang2, Huilong Duan2

  • 1School of Medicine, Zhejiang University, Hangzhou, China.

Frontiers in Genetics
|September 5, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces SNPMap, an automated tool that integrates and visualizes single-nucleotide polymorphism (SNP) data from multiple sources. SNPMap aids disease diagnosis and prognosis by providing clearer, integrated SNP interpretation for researchers.

Keywords:
precision medicinesingle-nucleotide polymorphismvariant interpretationvisualizationweb application

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Next-generation sequencing technologies generate vast amounts of single-nucleotide polymorphism (SNP) data, crucial for disease diagnosis and prognosis.
  • Current methods for curating and interpreting SNP data are often manual, time-consuming, costly, and require frequent updates.
  • Automated knowledge source curation can lead to information overload, hindering practical application.

Purpose of the Study:

  • To develop an automated pipeline for creating an integrated and visual single-nucleotide polymorphism (SNP) interpretation tool.
  • To address the challenges of manual data curation and information overload in SNP analysis.
  • To enhance the accessibility and clarity of SNP-related information for researchers.

Main Methods:

  • An automated pipeline was designed to periodically extract SNP-related information from databases like LitVar, PubTator, and the GWAS Catalog API.
  • Data underwent extraction, integration, and visualization processes to create the SNPMap tool.
  • Keywords and their semantic relationships to SNPs were visualized using graphs, with significance indicated by graph element size and width.

Main Results:

  • SNPMap successfully integrated and visualized SNP information from disparate sources.
  • The tool generated graphical representations of keyword-SNP relationships, aiding interpretation.
  • It calculated and sorted the most relevant SNPs for each keyword within the SNPMap system.

Conclusions:

  • SNPMap offers an automated solution for SNP data interpretation, overcoming limitations of manual curation.
  • The tool enhances user access to lucid and detailed SNP information through integrated visualization.
  • SNPMap facilitates improved disease diagnosis and prognosis by streamlining the analysis of complex genetic variant data.