A Computational Approach for Modeling the Allele Frequency Spectrum of Populations with Arbitrarily Varying Size.

Hua Chen

Abstract read

In one paragraph

Article in Genomics, proteomics & bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed

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1 citing paper in PubMed.

CEGA: a method for inferring natural selection by comparative population genomic analysis across species.Genome biology · 2023
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1 author.

Hua ChenCAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China; School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address: chenh@big.ac.cn.

Funding

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6 · The paper itself

Abstract

The allele frequency spectrum (AFS), or site frequency spectrum, is commonly used to summarize the genomic polymorphism pattern of a sample, which is informative for inferring population history and detecting natural selection. In 2013, Chen and Chen developed a method for analytically deriving the AFS for populations with temporally varying size through the coalescence time-scaling function. However, their approach is only applicable to population history scenarios in which the analytical form of the time-scaling function is tractable. In this paper, we propose a computational approach to extend the method to populations with arbitrary complex varying size by numerically approximating the time-scaling function. We demonstrate the performance of the approach by constructing the AFS for two population history scenarios: the logistic growth model and the Gompertz growth model, for which the AFS are unavailable with existing approaches. Software for implementing the algorithm can be downloaded at http://chenlab.big.ac.cn/software/.

Indexed as

Gene FrequencyAlgorithmsComputational BiologyGenetics, PopulationHumansModels, StatisticalPolymorphism, GeneticSample SizeAllele frequency spectrumCoalescentComplex demographyPopulation genetic inferencePopulation history

Identifiers

PMID32173599

DOI10.1016/j.gpb.2019.06.002

PMCPMC7212486

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