Estimating Sampling Selection Bias in Human Genetics: A Phenomenological Approach

Risso, Davide; Taglioli, Luca; Iasio, S. De; Gueresi, Paola; Alfani, Guido; Nelli, S.; Rossi, Paolo; Paoli, Giorgio; Tofanelli, Sergio

doi:10.1371/journal.pone.0140146

Cited by 4 publications

(4 citation statements)

References 20 publications

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“…American ancestry groups are typically younger than 750 generations (15,000 to 22,500 years), consistent with existing knowledge about the settlement of the Americas via the Bering land bridge that connected Asia and North America during the last glacial maximum around 15,000 to 23,000 years ago [45,46]. We note, however, that recent admixture and the sampling strategies of the different data sets [47,48] can have a strong impact on age distributions. For example, variants at high frequency within American populations but that are nevertheless restricted to just American and African populations are, on average, younger than lower-frequency variants (within American populations) with the same geographical restriction (S6 Fig).…”

Section: Distribution Of Allele Age In the Human Genomesupporting

confidence: 84%

Dating genomic variants and shared ancestry in population-scale sequencing data

2020

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The origin and fate of new mutations within species is the fundamental process underlying evolution. However, while much attention has been focused on characterizing the presence, frequency, and phenotypic impact of genetic variation, the evolutionary histories of most variants are largely unexplored. We have developed a nonparametric approach for estimating the date of origin of genetic variants in large-scale sequencing data sets. The accuracy and robustness of the approach is demonstrated through simulation. Using data from two publicly available human genomic diversity resources, we estimated the age of more than 45 million single-nucleotide polymorphisms (SNPs) in the human genome and release the Atlas of Variant Age as a public online database. We characterize the relationship between variant age and frequency in different geographical regions and demonstrate the value of age information in interpreting variants of functional and selective importance. Finally, we use allele age estimates to power a rapid approach for inferring the ancestry shared between individual genomes and to quantify genealogical relationships at different points in the past, as well as to describe and explore the evolutionary history of modern human populations.

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Section: Distribution Of Allele Age In the Human Genomesupporting

confidence: 84%

Dating genomic variants and shared ancestry in population-scale sequencing data

2020

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“…Variants restricted to American ancestry groups are typically younger than 750 generations (15,000 to 22,500 years), consistent with existing knowledge about the settlement of the Americas via the Bering land bridge that connected Asia and North America during the last glacial maximum around 15,000 to 23,000 years ago [42,43]. We note, however, that recent admixture and the sampling strategies of the different data sets [44,45] can have a strong impact on age distributions. For example, variants at high frequency within American populations, but which are nevertheless restricted to just American and African populations, are on average younger than lower frequency variants (within American populations) with the same geographical restriction (Supplementary Figure S6).…”

Section: Distribution Of Allele Age In the Human Genomesupporting

confidence: 83%

Dating genomic variants and shared ancestry in population-scale sequencing data

Albers

McVean

2018

Preprint

118

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The origin and fate of new mutations within species is the fundamental process underlying evolution. However, while much attention has been focused on characterizing the presence, frequency, and phenotypic impact of genetic variation, the evolutionary histories of most variants are largely unexplored. We have developed a nonparametric approach for estimating the date of origin of genetic variants in large-scale sequencing data sets. The accuracy and robustness of the approach is demonstrated through simulation. Using data from two publicly available human genomic diversity resources, we estimated the age of more than 45 million single nucleotide polymorphisms (SNPs) in the human genome and release the Atlas of Variant Age as a public online database. We characterize the relationship between variant age and frequency in different geographical regions, and demonstrate the value of age information in interpreting variants of functional and selective importance. Finally, we use allele age estimates to power a rapid approach for inferring the ancestry shared between individual genomes, to quantify genealogical relationships at different points in the past, as well as describe and explore the evolutionary history of modern human populations.

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“…Sampling bias can affect the allele variation and the allele frequencies at specific loci. Several studies have reported that sample selection bias can affect population studies, such as ethnic group classification and ancestry inference (Shringarpure and Xing 2014;Risso et al 2015). Even if the samples are derived from the same population, allele frequency and rare alleles can be affected by sample size, sampling bias, and heterozygosity ratio when performing population study.…”

Section: Resultsmentioning

confidence: 99%

Comparative analysis of allele variation using allele frequencies according to sample size in Korean population

2021

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Background Allele frequency using short tandem repeats (STRs) is used to calculate likelihood ratio for database match, to interpret DNA mixture and to estimate ethnic groups in forensic genetics. In Korea, three population studies for 23 STR loci have been conducted with different sample size for forensic purposes. Objective We performed comparative analysis to determine how the difference of sample size affects the allele frequency and allele variation within same ethnic population (i.e. Korean). Furthermore, this study was conducted to check how the sampling group and multiplex kit also affect allele variation such as rare alleles and population specific alleles. Methods To compare allele variation, we used allele frequencies of three population data published from three Korean forensic research groups. Allele frequencies were calculated using different sample sizes and multiplex kits: 526, 1000, and 2000 individuals, respectively. Results The results showed the different distribution of allele frequencies in some loci. There was also a difference in the number of rare alleles observed by the sample size and sampling bias. In particular, an allele of 9.1 in the D2S441 locus was not observed in population study with 526 individuals due to multiplex kits. Conclusion Because the allele frequencies play an important role in forensic genetics, even if the samples are derived from the same population, it is important to consider the effects of sample size, sampling bias, and selection of multiplex kits in population studies.

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Estimating Sampling Selection Bias in Human Genetics: A Phenomenological Approach

Cited by 4 publications

References 20 publications

Dating genomic variants and shared ancestry in population-scale sequencing data

Dating genomic variants and shared ancestry in population-scale sequencing data

Dating genomic variants and shared ancestry in population-scale sequencing data

Comparative analysis of allele variation using allele frequencies according to sample size in Korean population

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