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

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: Jul 4, 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 ID-info: SNP ID searching and visualization platform.

Cheng-Hong Yang1, Li-Yeh Chuang, Yu-Huei Cheng

  • 1Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Taiwan, ROC.

Omics : a Journal of Integrative Biology
|June 28, 2008
PubMed
Summary

This study introduces SNP ID-info, a freeware tool that identifies single nucleotide polymorphism (SNP) IDs using genomic data. It aids researchers in systematic SNP association studies by providing visualized SNP information.

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Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • Association studies often identify relationships between genetic variations like single nucleotide polymorphisms (SNPs) and diseases or cancers without providing specific SNP IDs.
  • This lack of direct SNP identification hinders systematic analysis and replication of genetic association findings.

Purpose of the Study:

  • To develop a user-friendly freeware tool, SNP ID-info, for efficiently retrieving SNP IDs from genomic and physical information.
  • To provide a visualized environment for SNP identification, aiding in complex genetic association studies.

Main Methods:

  • The SNP ID-info freeware incorporates functions such as "SNP-ePCR" for sequence generation, "SNPosition" for matching sequences to SNP IDs, and "SNP search" and "SNP fasta" for querying SNPs by cytogenetic band, contig position, or keywords.
  • The tool visualizes the SNP neighboring environment, ordered by contig position, and marks flanking hits, overcoming limitations of existing tools like NCBI SNP BLAST.

Main Results:

  • Successful development of SNP ID-info freeware, enabling the retrieval of SNP IDs from various genomic inputs.
  • The tool provides a comprehensive and visualized SNP identification environment, improving upon existing methods.

Conclusions:

  • SNP ID-info offers a valuable resource for researchers conducting systematic SNP association studies by simplifying SNP identification and visualization.
  • The freeware assists in overcoming challenges in SNP identification, thereby supporting advancements in understanding the genetic basis of diseases and cancers.