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Updated: Jun 25, 2026
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Infinium Assay for Large-scale SNP Genotyping Applications
Published on: November 19, 2013
Database mining for selection of SNP markers useful in admixture mapping
Tesfaye M Baye1, Hemant K Tiwari, David B Allison
1Human and Molecular Genetics Center, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. tmersha@mcw.edu
Biodata Mining
|February 17, 2009
Summary
Researchers identified ancestry informative markers (AIMs) using data mining of SNP databases. These AIMs are valuable for admixture mapping in complex human diseases and traits.
Area of Science:
- Genomics
- Human Genetics
- Population Genetics
Background:
- Simultaneous genotyping of hundreds of thousands of SNPs is now feasible.
- Publicly available genomic databases offer underutilized resources for identifying markers of complex human traits.
- Data mining SNP data is a viable strategy to find informative markers for ancestry.
Purpose of the Study:
- To identify Single Nucleotide Polymorphisms (SNPs) informative for ancestry using data mining.
- To prioritize candidate SNPs for admixture mapping in complex human diseases and traits.
- To leverage large-scale SNP data from public databases.
Main Methods:
- Investigated SNP distribution and density in African and European populations using HapMap, Affymetrix, and Illumina databases.
- Compared over 4 million SNPs between populations based on allele frequency difference (delta >or= 0.3).
- Employed data mining to identify potential candidate SNPs.
Main Results:
- Identified 15% of HapMap, 11% of Affymetrix, and 14% of Illumina SNP sets as ancestry informative markers (AIMs).
- AIM panels include rs numbers, allele frequencies, delta values, and map positions.
- All marker information is publicly available on a dedicated website.
Conclusions:
- The selected SNP sets are valuable resources for admixture mapping studies.
- Discusses the overlap of selected AIMs across different platforms based on marker informativeness.
- Highlights the utility of AIMs for understanding genetic variation in complex traits.
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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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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,...
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%...