Ascertainment biases in SNP chips affect measures of population divergence

TY - JOUR

T1 - Ascertainment biases in SNP chips affect measures of population divergence

AU - Albrechtsen, Anders

AU - Nielsen, Finn Cilius

AU - Nielsen, Rasmus

PY - 2010/11/1

Y1 - 2010/11/1

N2 - Chip-based high-throughput genotyping has facilitated genome-wide studies of genetic diversity. Many studies have utilized these large data sets to make inferences about the demographic history of human populations using measures of genetic differentiation such as F(ST) or principal component analyses. However, the single nucleotide polymorphism (SNP) chip data suffer from ascertainment biases caused by the SNP discovery process in which a small number of individuals from selected populations are used as discovery panels. In this study, we investigate the effect of the ascertainment bias on inferences regarding genetic differentiation among populations in one of the common genome-wide genotyping platforms. We generate SNP genotyping data for individuals that previously have been subject to partial genome-wide Sanger sequencing and compare inferences based on genotyping data to inferences based on direct sequencing. In addition, we also analyze publicly available genome-wide data. We demonstrate that the ascertainment biases will distort measures of human diversity and possibly change conclusions drawn from these measures in some times unexpected ways. We also show that details of the genotyping calling algorithms can have a surprisingly large effect on population genetic inferences. We not only present a correction of the spectrum for the widely used Affymetrix SNP chips but also show that such corrections are difficult to generalize among studies.

AB - Chip-based high-throughput genotyping has facilitated genome-wide studies of genetic diversity. Many studies have utilized these large data sets to make inferences about the demographic history of human populations using measures of genetic differentiation such as F(ST) or principal component analyses. However, the single nucleotide polymorphism (SNP) chip data suffer from ascertainment biases caused by the SNP discovery process in which a small number of individuals from selected populations are used as discovery panels. In this study, we investigate the effect of the ascertainment bias on inferences regarding genetic differentiation among populations in one of the common genome-wide genotyping platforms. We generate SNP genotyping data for individuals that previously have been subject to partial genome-wide Sanger sequencing and compare inferences based on genotyping data to inferences based on direct sequencing. In addition, we also analyze publicly available genome-wide data. We demonstrate that the ascertainment biases will distort measures of human diversity and possibly change conclusions drawn from these measures in some times unexpected ways. We also show that details of the genotyping calling algorithms can have a surprisingly large effect on population genetic inferences. We not only present a correction of the spectrum for the widely used Affymetrix SNP chips but also show that such corrections are difficult to generalize among studies.

KW - African Americans

KW - Asian Continental Ancestry Group

KW - Bias (Epidemiology)

KW - Europe

KW - Genetic Variation

KW - Genetics, Population

KW - Geography

KW - Haplotypes

KW - Humans

KW - Japan

KW - Likelihood Functions

KW - Oligonucleotide Array Sequence Analysis

KW - Polymorphism, Single Nucleotide

KW - Principal Component Analysis

KW - Sequence Analysis, DNA

U2 - 10.1093/molbev/msq148

DO - 10.1093/molbev/msq148

M3 - Journal article

C2 - 20558595

SN - 0737-4038

VL - 27

SP - 2534

EP - 2547

JO - Molecular Biology and Evolution

JF - Molecular Biology and Evolution

IS - 11

ER -