Premium
SNP ascertainment bias in population genetic analyses: Why it is important, and how to correct it
Author(s) -
Lachance Joseph,
Tishkoff Sarah A.
Publication year - 2013
Publication title -
bioessays
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.175
H-Index - 184
eISSN - 1521-1878
pISSN - 0265-9247
DOI - 10.1002/bies.201300014
Subject(s) - genotyping , tag snp , snp genotyping , linkage disequilibrium , genetics , biology , single nucleotide polymorphism , snp , allele frequency , population , sampling bias , allele , genotype , sample size determination , statistics , gene , medicine , mathematics , environmental health
Whole genome sequencing and SNP genotyping arrays can paint strikingly different pictures of demographic history and natural selection. This is because genotyping arrays contain biased sets of pre‐ascertained SNPs. In this short review, we use comparisons between high‐coverage whole genome sequences of African hunter‐gatherers and data from genotyping arrays to highlight how SNP ascertainment bias distorts population genetic inferences. Sample sizes and the populations in which SNPs are discovered affect the characteristics of observed variants. We find that SNPs on genotyping arrays tend to be older and present in multiple populations. In addition, genotyping arrays cause allele frequency distributions to be shifted towards intermediate frequency alleles, and estimates of linkage disequilibrium are modified. Since population genetic analyses depend on allele frequencies, it is imperative that researchers are aware of the effects of SNP ascertainment bias. With this in mind, we describe multiple ways to correct for SNP ascertainment bias.