2022
DOI: 10.1101/2022.06.14.496083
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GADMA2: more efficient and flexible demographic inference from genetic data

Abstract: Inference of complex demographic histories typically requires parameterized models specified manually by the researcher. With an increased variety of methods and tools, each with its own interface, model specification becomes tedious and error-prone. Moreover, optimization algorithms used to find optimal parameters sometimes turn out to be inefficient. The open source software GADMA addresses these problems, providing automatic demographic inference. It proposes a common interface for several simulation engine… Show more

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Cited by 10 publications
(12 citation statements)
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“…To quantify the extent of temporal change in genetic diversity and migration rates among populations, we next fit a series of demographic models to the three‐dimensional site frequency spectrum (SFS) of eastern California ( P. s. nevadensis ), Bay Area ( P. s. alaudinus ), and Newport Bay ( P. s. beldingi ) birds in GADMA2 (Noskova et al., 2023). We ran separate analyses for a historic dataset and a modern dataset of these three populations.…”
Section: Methodsmentioning
confidence: 99%
“…To quantify the extent of temporal change in genetic diversity and migration rates among populations, we next fit a series of demographic models to the three‐dimensional site frequency spectrum (SFS) of eastern California ( P. s. nevadensis ), Bay Area ( P. s. alaudinus ), and Newport Bay ( P. s. beldingi ) birds in GADMA2 (Noskova et al., 2023). We ran separate analyses for a historic dataset and a modern dataset of these three populations.…”
Section: Methodsmentioning
confidence: 99%
“…The parameters in the demographic model were inferred using GADMA ver. 2 ( 80 ), which employs a genetic algorithm to optimize parameter values. As an engine in the inference we used Moments ( 81 ), which fits the observed joint MAF spectrum to simulated data using ordinary differential equations.…”
Section: Methodsmentioning
confidence: 99%
“…To test for the presence of gene flow exceeding potential thresholds for homogenizing population structure, we estimated a model accounting for divergence times, effective population sizes, and migration rates between current and ancestral lineages. We optimized a three‐population demographic model based on the site‐frequency spectrum (SFS) using the genetic algorithm “GADMA” (Noskova et al., 2020, 2023) based on the “moments” engine (Jouganous et al., 2017). We first down projected the VCF file from ipyrad to a three‐dimensional SFS of [27,9,21] allele counts from (28,8,20) diploid individuals from the NTA, COH, and CHR lineages (see Section 3) using “easySFS” (https://github.com/isaacovercast/easySFS; Gutenkunst et al., 2009).…”
Section: Methodsmentioning
confidence: 99%