Benchmarking kinship estimation tools for ancient genomes using pedigree simulations

Date

2024-04-27

Author

Akturk, Sevval
Mapelli, Igor
Guler, Murat
Gurun, Kanat
Katircioglu, Buesra
Vural, Kivilcim Basak
Saglican, Ekin
Cetin, Mehmet
Yaka, Reyhan
Sürer, Elif
Atag, Gozde
Cokoglu, Sevim Seda
Sevkar, Arda
Altinisik, N. Ezgi
Koptekin, Dilek
Somel, Mehmet

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There is growing interest in uncovering genetic kinship patterns in past societies using low-coverage palaeogenomes. Here, we benchmark four tools for kinship estimation with such data: lcMLkin, NgsRelate, KIN, and READ, which differ in their input, IBD estimation methods, and statistical approaches. We used pedigree and ancient genome sequence simulations to evaluate these tools when only a limited number (1 to 50 K, with minor allele frequency >= 0.01) of shared SNPs are available. The performance of all four tools was comparable using >= 20 K SNPs. We found that first-degree related pairs can be accurately classified even with 1 K SNPs, with 85% F-1 scores using READ and 96% using NgsRelate or lcMLkin. Distinguishing third-degree relatives from unrelated pairs or second-degree relatives was also possible with high accuracy (F-1 > 90%) with 5 K SNPs using NgsRelate and lcMLkin, while READ and KIN showed lower success (69 and 79% respectively). Meanwhile, noise in population allele frequencies and inbreeding (first-cousin mating) led to deviations in kinship coefficients, with different sensitivities across tools. We conclude that using multiple tools in parallel might be an effective approach to achieve robust estimates on ultra-low-coverage genomes.

URI

https://hdl.handle.net/11511/109697

Collections

Graduate School of Informatics, Article