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Database mining for selection of SNP markers useful in admixture mapping

Overview of attention for article published in BioData Mining, February 2009
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Title
Database mining for selection of SNP markers useful in admixture mapping
Published in
BioData Mining, February 2009
DOI 10.1186/1756-0381-2-1
Pubmed ID
Authors

Tesfaye M Baye, Hemant K Tiwari, David B Allison, Rodney C Go

Abstract

New technologies make it possible for the first time to genotype hundreds of thousands of SNPs simultaneously. A wealth of genomic information in the form of publicly available databases is underutilized as a potential resource for uncovering functionally relevant markers underlying complex human traits. Given the huge amount of SNP data available from the annotation of human genetic variation, data mining is a reasonable approach to investigating the number of SNPs that are informative for ancestry information. The distribution and density of SNPs across the genome of African and European populations were extensively investigated by using the HapMap, Affymetrix, and Illumina SNP databases. We exploited these resources by mining the data available from each of these databases to prioritize potential candidate SNPs useful for admixture mapping in complex human diseases and traits. Over 4 million SNPs were compared between Africans and Europeans on the basis of a pre-specified recommended allele frequency difference (delta) value of >or= 0.3. The method identified 15% of HapMap, 11% of Affymetrix, and 14% of Illumina SNP sets as candidate SNPs, termed ancestry informative markers (AIMs). These AIM panels with assigned rs numbers, allele frequencies in each ethnic group, delta value, and map positions are all posted on our website http://www.ssg.uab.edu/downloads/admixture_mapping/SNPAIMs.txt. All marker information in this data set is freely and publicly available without restriction. The selected SNP sets represent valuable resources for admixture mapping studies. The overlap between selected AIMs by this single measure of marker informativeness in the different platforms is discussed.

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Geographical breakdown

Country Count As %
Brazil 3 5%
United Kingdom 2 3%
Germany 1 2%
Australia 1 2%
Switzerland 1 2%
Uruguay 1 2%
United States 1 2%
Unknown 50 83%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 35%
Student > Ph. D. Student 12 20%
Student > Postgraduate 5 8%
Professor > Associate Professor 4 7%
Student > Bachelor 3 5%
Other 13 22%
Unknown 2 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 48%
Biochemistry, Genetics and Molecular Biology 10 17%
Computer Science 6 10%
Medicine and Dentistry 5 8%
Psychology 2 3%
Other 3 5%
Unknown 5 8%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 February 2019.
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#15,498,204
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Outputs from BioData Mining
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#145,970
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Outputs of similar age from BioData Mining
#1
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