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Updated: Jul 19, 2026
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Infinium Assay for Large-scale SNP Genotyping Applications
Published on: November 19, 2013
Individual SNP allele reconstruction from informative markers selected by a non-linear Gauss-type algorithm
Valentina Moskvina1, Karl Michael Schmidt
1Department of Psychological Medicine, College of Medicine, Cardiff University, Cardiff, UK. MoskvinaV1@cardiff.ac.uk
Human Heredity
|October 19, 2006
Summary
Selecting optimal single nucleotide polymorphism (SNP) markers is crucial for genetic association studies. A new algorithm ensures selected markers fully represent the genome, enabling direct association analysis and improved study design.
Area of Science:
- Genetics
- Bioinformatics
- Statistical genomics
Background:
- Selecting maximally informative single nucleotide polymorphism (SNP) markers is essential for genome-wide association studies (GWAS).
- Current methods using pairwise correlations or subset informativity do not fully capture marker relationships.
- Reducing tag markers using haplotype information complicates association analysis interpretation.
Purpose of the Study:
- To develop an optimal marker selection algorithm for association studies.
- To ensure selected markers allow for the reconstruction of all other markers.
- To facilitate direct inference of allelic association.
Main Methods:
- A non-linear Gauss-type algorithm is proposed for marker selection.
- The method optimizes informativity measures and allows explicit marker reconstruction.
- The algorithm is based on population haplotype distribution but adaptable to unphased genotypes.
Main Results:
- The algorithm selects an optimal subset of markers based on informativity.
- Selected markers enable explicit reconstruction of all other known markers.
- Direct inference of allelic association is permitted by the selected markers.
Conclusions:
- The proposed algorithm offers a rational approach to informative marker selection.
- It allows for controlled optimization of information content and full marker reconstruction.
- The reconstruction step can validate existing tag markers from other selection methods.
Related Concept Videos
01:05Single 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,...
01:11Genome-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...
GWAS does not require the identification of the target gene involved in...
02:26Comparing 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%...
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%...
02:54Evolutionary Relationships through Genome Comparisons
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...