Estimating inbreeding coefficients from NGS data: impact on genotype calling and allele frequency estimation

Filipe Jorge Garrett Vieira; Matteo Fumagalli; Anders Albrechtsen; Rasmus Nielsen

doi:10.1101/gr.157388.113

Estimating inbreeding coefficients from NGS data: impact on genotype calling and allele frequency estimation

Filipe Jorge Garrett Vieira, Matteo Fumagalli, Anders Albrechtsen, Rasmus Nielsen

Bioinformatik og RNA Biologi

45 Citationer (Scopus)

Abstract

Most methods for Next-Generation Sequencing (NGS) data analyses incorporate information regarding allele frequencies using the assumption of Hardy-Weinberg Equilibrium (HWE) as a prior. However, many organisms including domesticated, partially selfing or with asexual life cycles show strong deviations from HWE. For such species, and specially for low coverage data, it is necessary to obtain estimates of inbreeding coefficients (F) for each individual beforecalling genotypes. Here, we present two methods for estimating inbreeding coefficients from NGS data based on an Expectation-Maximization (EM) algorithm. We assess the impact of taking inbreeding into account when calling genotypes or estimating the Site Frequency Spectrum (SFS), and demonstrate a marked increase in accuracy on low coverage highly inbred samples. We demonstrate the applicability and efficacy of these methods in both simulated and real datasets.

Originalsprog	Engelsk
Tidsskrift	Genome Research
Vol/bind	23
Sider (fra-til)	1852-1861
Antal sider	10
ISSN	1088-9051
DOI	https://doi.org/10.1101/gr.157388.113
Status	Udgivet - nov. 2013

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10.1101/gr.157388.113

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title = "Estimating inbreeding coefficients from NGS data: impact on genotype calling and allele frequency estimation",

abstract = "Most methods for next-generation sequencing (NGS) data analyses incorporate information regarding allele frequencies using the assumption of Hardy-Weinberg equilibrium (HWE) as a prior. However, many organisms including those that are domesticated, partially selfing, or with asexual life cycles show strong deviations from HWE. For such species, and specially for low-coverage data, it is necessary to obtain estimates of inbreeding coefficients (F ) for each individual before calling genotypes. Here, we present two methods for estimating inbreeding coefficients from NGS data based on an expectation-maximization (EM) algorithm. We assess the impact of taking inbreeding into account when calling genotypes or estimating the site frequency spectrum (SFS), and demonstrate a marked increase in accuracy on low-coverage highly inbred samples. We demonstrate the applicability and efficacy of these methods in both simulated and real data sets.",

author = "{Garrett Vieira}, {Filipe Jorge} and Matteo Fumagalli and Anders Albrechtsen and Rasmus Nielsen",

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T1 - Estimating inbreeding coefficients from NGS data

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AU - Garrett Vieira, Filipe Jorge

AU - Fumagalli, Matteo

AU - Albrechtsen, Anders

AU - Nielsen, Rasmus

PY - 2013/11

Y1 - 2013/11

N2 - Most methods for next-generation sequencing (NGS) data analyses incorporate information regarding allele frequencies using the assumption of Hardy-Weinberg equilibrium (HWE) as a prior. However, many organisms including those that are domesticated, partially selfing, or with asexual life cycles show strong deviations from HWE. For such species, and specially for low-coverage data, it is necessary to obtain estimates of inbreeding coefficients (F ) for each individual before calling genotypes. Here, we present two methods for estimating inbreeding coefficients from NGS data based on an expectation-maximization (EM) algorithm. We assess the impact of taking inbreeding into account when calling genotypes or estimating the site frequency spectrum (SFS), and demonstrate a marked increase in accuracy on low-coverage highly inbred samples. We demonstrate the applicability and efficacy of these methods in both simulated and real data sets.

AB - Most methods for next-generation sequencing (NGS) data analyses incorporate information regarding allele frequencies using the assumption of Hardy-Weinberg equilibrium (HWE) as a prior. However, many organisms including those that are domesticated, partially selfing, or with asexual life cycles show strong deviations from HWE. For such species, and specially for low-coverage data, it is necessary to obtain estimates of inbreeding coefficients (F ) for each individual before calling genotypes. Here, we present two methods for estimating inbreeding coefficients from NGS data based on an expectation-maximization (EM) algorithm. We assess the impact of taking inbreeding into account when calling genotypes or estimating the site frequency spectrum (SFS), and demonstrate a marked increase in accuracy on low-coverage highly inbred samples. We demonstrate the applicability and efficacy of these methods in both simulated and real data sets.

U2 - 10.1101/gr.157388.113

DO - 10.1101/gr.157388.113

M3 - Journal article

C2 - 23950147

SN - 1088-9051

VL - 23

SP - 1852

EP - 1861

JO - Genome Research

JF - Genome Research

ER -

Estimating inbreeding coefficients from NGS data: impact on genotype calling and allele frequency estimation

Abstract

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