Correcting for ascertainment biases when analyzing SNP data: applications to the estimation of linkage disequilibrium.
As large-scale sequencing efforts turn from single genome sequencing to polymorphism discovery, single nucleotide polymorphisms (SNPs) are becoming an increasingly important class of population genetic data. But because of the ascertainment biases introduced by many methods of SNP discovery, most SNP data cannot be analyzed using classical population genetic methods. Statistical methods must instead be developed that can explicitly take into account each method of SNP discovery. Here we review some of the current methods for analyzing SNPs and derive sampling distributions for single SNPs and pairs of SNPs for some common SNP discovery schemes. We also show that the ascertainment scheme has a large effect on the estimation of linkage disequilibrium and recombination, and describe some methods of correcting for ascertainment biases when estimating recombination rates from SNP data.
Nielsen
Rasmus
R
Department of Biometrics, Cornell University, 439 Warren Hall, Ithaca, NY 14853-7801, USA. rn28@cornell.edu
Signorovitch
James
J
D015982:Bias; D005828:Genetics, Population / Q000706:statistics & numerical data*; D006801:Humans; D015810:Linkage Disequilibrium; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D014481:United States