2023
DOI: 10.1093/ve/vead033
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Mutation rate, selection, and epistasis inferred from RNA virus haplotypes via neural posterior estimation

Abstract: RNA viruses are particularly notorious for their high levels of genetic diversity, which is generated through the forces of mutation and natural selection. However, disentangling these two forces is a considerable challenge, and this may lead to widely divergent estimates of viral mutation rates, as well as difficulties in inferring fitness effects of mutations. Here, we develop, test, and apply an approach aimed at inferring the mutation rate and key parameters that govern natural selection, from haplotype se… Show more

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Cited by 4 publications
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“…Despite this 𝑠 𝐶 δ 𝐶 under-confidence, the posterior distributions are narrow in biological terms: the 95% HDI represents less than an order of magnitude for both and . Thus, we did not apply post-training adjustments to the neural density estimator, such as 𝑠 𝐶 δ 𝐶 calibration (Cook et al, 2006) or ensembles (Caspi et al, 2023;Hermans et al, 2022).…”
Section: Breakpoint Analysis and Cnv Mechanism Inference In Sequenced...mentioning
confidence: 99%
“…Despite this 𝑠 𝐶 δ 𝐶 under-confidence, the posterior distributions are narrow in biological terms: the 95% HDI represents less than an order of magnitude for both and . Thus, we did not apply post-training adjustments to the neural density estimator, such as 𝑠 𝐶 δ 𝐶 calibration (Cook et al, 2006) or ensembles (Caspi et al, 2023;Hermans et al, 2022).…”
Section: Breakpoint Analysis and Cnv Mechanism Inference In Sequenced...mentioning
confidence: 99%