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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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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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Related Experiment Video

Updated: May 3, 2026

Infinium Assay for Large-scale SNP Genotyping Applications
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Coverage and efficiency in current SNP chips.

Ngoc-Thuy Ha1, Saskia Freytag2, Heike Bickeboeller2

  • 11] Department of Genetic Epidemiology, University Medical Centre Goettingen, Goettingen, Germany [2] Department of Animal Sciences, Animal Breeding and Genetics Group, Georg-August-University Goettingen, Goettingen, Germany.

European Journal of Human Genetics : EJHG
|January 23, 2014
PubMed
Summary
This summary is machine-generated.

Choosing the best SNP chip for genome coverage on a budget is crucial. Affymetrix population-optimized arrays offer cost-effective options for Asian and African populations, while Illumina

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Area of Science:

  • Genomics
  • Population Genetics
  • Bioinformatics

Background:

  • High-density SNP chips are essential tools for genetic research.
  • Evaluating cost-effectiveness alongside genetic coverage is critical for budget-conscious studies.
  • Previous comparisons often overlooked economic factors and population-specific performance.

Purpose of the Study:

  • To determine the most cost-effective high-density SNP chip for human genome coverage across diverse populations.
  • To compare the performance of 12 commercial SNP chips from Affymetrix and Illumina.
  • To assess genetic coverage, efficiency, and cost-benefit ratios for European, Asian, and African populations.

Main Methods:

  • Comparative analysis of 12 Affymetrix and Illumina SNP chips.
  • Development and application of efficiency and cost-benefit ratio metrics.
  • Utilized the 1000 Genomes Project as a reference population dataset.
  • Evaluated chips for European, Asian, and African populations.

Main Results:

  • Affymetrix population-optimized arrays provide the most cost-effective coverage for Asian and African populations.
  • Illumina Human Omni 2.5-8 is the preferred chip for European population coverage.
  • An Affymetrix Eastern Asian subpopulation chip demonstrated broad utility across all investigated populations.
  • Actual genetic coverage estimates were lower than manufacturer claims for all tested chips.

Conclusions:

  • SNP chip selection should prioritize cost-benefit and population-specific performance.
  • Affymetrix and Illumina offer distinct advantages depending on the target population and budget.
  • Manufacturer-reported SNP coverage may overestimate actual genomic utility.