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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...
Genomic Imprinting and Inheritance02:30

Genomic Imprinting and Inheritance

Diploid organisms inherit genetic material through chromosomes from both parents. Copies of the same gene are known as alleles. In most cases, both alleles are simultaneously expressed and allow various cellular processes to function optimally. If one of the alleles is missing or mutated, the expression of the other allele can compensate; however, this is not true for all genes.
The expression of some genes depends on which parent passed the gene to the offspring, through a phenomenon known as...
Overview of Transposition and Recombination02:13

Overview of Transposition and Recombination

Transposons make up a significant part of genomes of various organisms. Therefore, it is believed that transposition played a major evolutionary role in speciation by changing genome sizes and modifying gene expression patterns. For example, in bacteria, transposition can lead to conferring antibiotic resistance. Movement of transposable elements within the genetic pool of pathogenic bacteria can aid in transfer of antibiotic-resistant genetic elements. In eukaryotes, transposons can carry out...

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Related Experiment Video

Updated: May 15, 2026

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
09:34

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

A comprehensive SNP and indel imputability database.

Qing Duan1, Eric Yi Liu, Damien C Croteau-Chonka

  • 1Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.

Bioinformatics (Oxford, England)
|January 8, 2013
PubMed
Summary
This summary is machine-generated.

A new database provides SNP and indel imputability information, improving genome-wide association studies (GWAS) efficiency. This tool helps researchers predict imputation accuracy without performing computationally intensive imputation, saving significant resources.

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Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

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Last Updated: May 15, 2026

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
09:34

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

Area of Science:

  • Genomics
  • Bioinformatics
  • Statistical Genetics

Background:

  • Genotype imputation is crucial for genome-wide association studies (GWAS), but accuracy depends on reference panels, leading to high computational costs.
  • Existing methods require actual imputation to assess accuracy, creating a need for pre-imputation quality assessment tools.
  • The 1000 Genomes Project provides a vast resource for variant discovery, necessitating efficient ways to evaluate their imputability.

Purpose of the Study:

  • To establish a publicly accessible database for SNP and indel imputability information.
  • To provide direct access to imputation accuracy predictions for markers across diverse populations and genotyping platforms.
  • To enable researchers to assess variant quality before conducting computationally expensive imputation.

Main Methods:

  • Developed a user-friendly interface for querying variant imputability by ID or genomic region.
  • Integrated data from the 1000 Genomes Project covering four major populations.
  • Enabled query refinement based on specific genome-wide association study genotyping platforms.

Main Results:

  • The database offers variant imputability information stratified by continental group and genotyping platform.
  • Demonstrated high predictive accuracy in Filipino individuals (AUCs ranging from 0.79 to 0.97) across different minor allele frequencies.
  • Showcased significant computational cost reduction (up to 48.6%) by filtering poorly imputable markers while retaining most well-imputed ones.

Conclusions:

  • The developed imputability database is the first to provide platform- and population-specific accuracy information.
  • This resource facilitates efficient GWAS by allowing researchers to prioritize high-quality variants and avoid unnecessary imputation.
  • The database significantly reduces computational burden and improves the overall efficiency of genetic association studies.