2022
DOI: 10.1093/g3journal/jkac040
|View full text |Cite
|
Sign up to set email alerts
|

Population divergence time estimation using individual lineage label switching

Abstract: Divergence time estimation from multilocus genetic data has become common in population genetics and phylogenetics. We present a new Bayesian inference method that treats the divergence time as a random variable. The divergence time is calculated from an assembly of splitting events on individual lineages in a genealogy. The time for such a splitting event is drawn from a hazard function of the truncated normal distribution. This allows easy integration into the standard coalescence framework used in programs … Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2023
2023
2023
2023

Publication Types

Select...
4

Relationship

1
3

Authors

Journals

citations
Cited by 4 publications
(2 citation statements)
references
References 24 publications
0
2
0
Order By: Relevance
“…To assess the direction and magnitude of migration across five replicate contact zones within the broader hybrid zone, MIGRATE‐n v4.4 (Beerli et al, 2022 ) was used to analyze Anchored Hybrid Enrichment (AHE) sequence data of P . feriarum from a previous study (Banker et al, 2020 ).…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…To assess the direction and magnitude of migration across five replicate contact zones within the broader hybrid zone, MIGRATE‐n v4.4 (Beerli et al, 2022 ) was used to analyze Anchored Hybrid Enrichment (AHE) sequence data of P . feriarum from a previous study (Banker et al, 2020 ).…”
Section: Methodsmentioning
confidence: 99%
“…To assess the direction and magnitude of migration across five replicate contact zones within the broader hybrid zone, MIGRATE-n v4.4 (Beerli et al, 2022) was used to analyze Anchored Hybrid Enrichment (AHE) sequence data of P. feriarum from a previous study (Banker et al, 2020). MIGRATE-n is a Bayesian coalescent-based algorithm that estimates the mutation-scaled population sizes (θ) and mutationscaled gene flow rates (M) among populations (Beerli et al, 2019); θ is 4 times the effective population size times the mutation rate per site and generation, M is a ratio between the immigration rate and the mutation rate, we assume that the mutation rate is the same among all species and we use θ and M instead of absolute numbers.…”
Section: Directionality Of Gene Flowmentioning
confidence: 99%