Modeling SNP array ascertainment with Approximate Bayesian Computation for demographic inference

Scientific Reports
Consuelo D Quinto-CortésMichael F Hammer

Abstract

Single nucleotide polymorphisms (SNPs) in commercial arrays have often been discovered in a small number of samples from selected populations. This ascertainment skews patterns of nucleotide diversity and affects population genetic inferences. We propose a demographic inference pipeline that explicitly models the SNP discovery protocol in an Approximate Bayesian Computation (ABC) framework. We simulated genomic regions according to a demographic model incorporating parameters for the divergence of three well-characterized HapMap populations and recreated the SNP distribution of a commercial array by varying the number of haploid samples and the allele frequency cut-off in the given regions. We then calculated summary statistics obtained from both the ascertained and genomic data and inferred ascertainment and demographic parameters. We implemented our pipeline to study the admixture process that gave rise to the present-day Mexican population. Our estimate of the time of admixture is closer to the historical dates than those in previous works which did not consider ascertainment bias. Although the use of whole genome sequences for demographic inference is becoming the norm, there are still underrepresented areas of the world fr...Continue Reading

References

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Citations

Mar 7, 2019·Molecular Biology and Evolution·Ariella L Gladstein, Michael F Hammer
Mar 31, 2021·PloS One·Johannes GeibelHenner Simianer

Methods Mentioned

BETA
genotyping
PCA

Related Concepts

Whole Genome Sequencing
Bayesian Prediction
Single Nucleotide Polymorphism
African Continental Ancestry Group
European Continental Ancestry Group
Korean Race
Alleles
Base Sequence
Genome
Mexican

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