2026-10-21T11:41:17Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/114332026-02-26T01:05:48Zcom_10259.4_2532com_10259.4_2477com_10259.4_106com_10259_2604col_10259.4_2533
Repositorio Institucional de la Universidad de Burgos
author
Mas Sandoval, Alex
author
Pope, Nathaniel S
author
Nielsen, Knud Nor
author
Altinkaya, Isin
author
Fumagalli, Matteo
author
Korneliussen, Thorfinn Sand
2026-02-25T17:11:40Z
2026-02-25T17:11:40Z
2022-05
2047-217X
https://hdl.handle.net/10259/11433
10.1093/gigascience/giac032
2047-217X
Background:
The site frequency spectrum summarizes the distribution of allele frequencies throughout the genome, and it is widely used as a summary statistic to infer demographic parameters and to detect signals of natural selection. The use of high-throughput low-coverage DNA sequencing data can lead to biased estimates of the site frequency spectrum due to high levels of uncertainty in genotyping.
Results:
Here we design and implement a method to efficiently and accurately estimate the multidimensional joint site frequency spectrum for large numbers of haploid or diploid individuals across an arbitrary number of populations, using low-coverage sequencing data. The method maximizes a likelihood function that represents the probability of the sequencing data observed given a multidimensional site frequency spectrum using genotype likelihoods. Notably, it uses an advanced binning heuristic paired with an accelerated expectation-maximization algorithm for a fast and memory-efficient computation, and can generate both unfolded and folded spectra and bootstrapped replicates for haploid and diploid genomes. On the basis of extensive simulations, we show that the new method requires remarkably less storage and is faster than previous implementations whilst retaining the same accuracy. When applied to low-coverage sequencing data from the fungal pathogen Neonectria neomacrospora, results recapitulate the patterns of population differentiation generated using the original high-coverage data.
Conclusion:
The new implementation allows for accurate estimation of population genetic parameters from arbitrarily large, low-coverage datasets, thus facilitating cost-effective sequencing experiments in model and non-model organisms.
eng
Atribución 4.0 Internacional
Site frequency spectrum
High-throughput sequencing
Genotype likelihoods
Next-generation sequencing
Maximum likelihood
Population genetics
Threading
Fast and accurate estimation of multidimensional site frequency spectra from low-coverage high-throughput sequencing data
info:eu-repo/semantics/article
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URL
https://riubu.ubu.es/bitstream/10259/11433/1/Mas-GigaScience_2022.pdf
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Mas-GigaScience_2022.pdf