BMCGenomics2015 Dodds.pdf (1.77 MB)

Construction of relatedness matrices using genotyping-by-sequencing data

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posted on 2023-05-03, 21:39 authored by Ken Dodds, John McEwanJohn McEwan, Rudiger BrauningRudiger Brauning, Rayna AndersonRayna Anderson, Tracey Van StijnTracey Van Stijn, Theódór Kristjánsson, Shannon ClarkeShannon Clarke
Background Genotyping-by-sequencing (GBS) is becoming an attractive alternative to array-based methods for genotyping individuals for a large number of single nucleotide polymorphisms (SNPs). Costs can be lowered by reducing the mean sequencing depth, but this results in genotype calls of lower quality. A common analysis strategy is to filter SNPs to just those with sufficient depth, thereby greatly reducing the number of SNPs available. We investigate methods for estimating relatedness based on GBS of low depth using theoretical calculation, simulation and application to a real data set. Results We show that unbiased estimates of relatedness can be obtained by using only those SNPs with genotype calls in both individuals. The expected value of this estimator is independent of the SNP depth in each individual, under a model of genotype calling that includes the special case of the two alleles being read at random. In contrast, the estimator of self-relatedness does depend on the SNP depth, and we provide a modification to provide unbiased estimates of self-relatedness. The estimators can be calculated using matrix methods, which allow efficient computation. Simulation results were consistent with the methods being unbiased, and suggest that the optimal sequencing depth is around 2-4 for relatedness between individuals and 5-10 for self-relatedness. Application to a real data set revealed that some SNP filtering may still be necessary, but for the exclusion of SNPs which did not behave in a Mendelian fashion. A simple graphical method (a ‘fin-plot’) is given to illustrate this issue and to guide filtering parameters. Conclusion We provide a method which gives unbiased estimates of relatedness, based on SNPs assayed by GBS, which accounts for the depth (including zero depth) of the genotype calls. This allows GBS to be applied at read depths which can be chosen to optimise the information obtained. SNPs with excess heterozygosity, often due to (partial) polyploidy or other duplications can be filtered based on a simple graphical method.


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© 2015 Dodds et al. Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.


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BioMed Central Ltd

Journal title

BMC Genomics




Dodds, K. G., McEwan, J. C., Brauning, R., Anderson, R. M., van Stijn, T. C., Kristjánsson, T., & Clarke, S. M. (2015). Construction of relatedness matrices using genotyping-by-sequencing data. BMC Genomics, 16, 1047. doi:10.1186/s12864-015-2252-3


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