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Related Concept Videos

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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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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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
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FastTagger: an efficient algorithm for genome-wide tag SNP selection using multi-marker linkage disequilibrium.

Guimei Liu1, Yue Wang, Limsoon Wong

  • 1Department of Computer Science, National University of Singapore, Singapore. liugm@comp.nus.edu.sg

BMC Bioinformatics
|February 2, 2010
PubMed
Summary
This summary is machine-generated.

FastTagger efficiently selects tag SNPs using multi-marker linkage disequilibrium (LD), significantly reducing computation time and memory usage. This new algorithm enables analysis of larger genomic regions for genetic association studies.

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Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Millions of common single nucleotide polymorphisms (SNPs) in the human genome are crucial for understanding genetic variations and diseases.
  • Linkage disequilibrium (LD) means many SNPs are correlated, allowing tag SNPs to represent larger sets for association studies.
  • Existing algorithms using pairwise LD are common, but multi-marker LD offers further reduction in tag SNPs, though often computationally intensive.

Purpose of the Study:

  • To develop an efficient algorithm for selecting tag SNPs based on multi-marker LD.
  • To overcome the time and memory limitations of existing multi-marker LD algorithms.
  • To enable tag SNP selection for large genomic regions ( > 100k SNPs) using length-3 tagging rules.

Main Methods:

  • Proposed FastTagger, an efficient algorithm for calculating multi-marker tagging rules and selecting tag SNPs.
  • Implemented techniques to reduce running time and memory consumption.
  • Evaluated performance on chromosomes with over 100k SNPs using length-3 tagging rules.

Main Results:

  • FastTagger is several times faster and consumes significantly less memory than existing multi-marker algorithms.
  • Achieved a 3%-9% reduction in tag SNPs compared to existing methods using length-3 rules.
  • Generated tagging rules showed high accuracy (>96% at r2 >= 0.9) for genotype imputation.

Conclusions:

  • FastTagger provides a practical and scalable solution to the computational bottleneck in multi-marker tag SNP selection.
  • Enables efficient analysis of large genomic datasets for genetic association studies.
  • Facilitates accurate genotype imputation through its generated tagging rules.