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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.
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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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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.
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DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
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Infinium Assay for Large-scale SNP Genotyping Applications
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Producing High-Quality Single Nucleotide Polymorphism Data for Genome-Wide Association Studies.

Philipp E Bayer1, Mitchell Gill1, Monica F Danilevicz1

  • 1Applied Bioinformatics Group, School of Biological Sciences, The University of Western Australia, Perth, WA, Australia.

Methods in Molecular Biology (Clifton, N.J.)
|May 31, 2022
PubMed
Summary

Quality control of single-nucleotide polymorphism (SNP) data is crucial for accurate genetic studies. This protocol details essential steps to minimize errors in downstream genomic analysis, ensuring reliable research findings.

Keywords:
FilteringPlinkQuality controlSNPsbcftoolsvcftools

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Area of Science:

  • Genetics
  • Genomics
  • Bioinformatics

Background:

  • Single-nucleotide polymorphisms (SNPs) are key molecular genetic markers in diverse genetic and genomic studies.
  • SNPs are utilized in genome-wide association studies for trait identification, population structure analysis, and evolutionary studies.

Purpose of the Study:

  • To outline a protocol for the quality control of SNP data.
  • To minimize errors in downstream genetic and genomic analyses.

Main Methods:

  • The study describes a protocol for SNP data quality control.
  • Focuses on essential steps following SNP discovery.

Main Results:

  • Implementation of the described quality control protocol minimizes errors in SNP data.
  • Ensures higher accuracy in downstream genetic and genomic analyses.

Conclusions:

  • Effective quality control of SNP data is a critical first step in SNP-based workflows.
  • This protocol enhances the reliability of genetic and genomic research outcomes.