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Obtaining Unbiased Estimates of Tagging SNP Performance
Author(s) -
Iles M. M.
Publication year - 2006
Publication title -
annals of human genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.537
H-Index - 77
eISSN - 1469-1809
pISSN - 0003-4800
DOI - 10.1111/j.1529-8817.2005.00212.x
Subject(s) - snp , sample size determination , set (abstract data type) , single nucleotide polymorphism , computer science , statistics , mathematics , computational biology , genetics , biology , genotype , gene , programming language
Summary The use of tagging SNPs (tSNPs) as a cost‐effective means of capturing genetic diversity is widespread. However, the quality of the tSNPs selected is dependent on the initial sample in which they are characterized. If the initial marker set is too sparse the tSNPs chosen will capture less information than a naïve analysis suggests. A simple method has been proposed that should provide a better estimate of the performance of tSNPs. It is shown here that this approach is both unbiased and accurate, even for small numbers of typed markers. The effect of unknown phase is also investigated and it is shown that, excepting very small samples, this has little effect on the accuracy of the method.