Demographic History
Demographic History
Demographic History
Visualization
drawn by demes [Gower et al. 2022]
Demographic Inference
Demographic Inference
Demographic Inference
Tools
GADMA — Global search Algorithm for Demographic Model Analysis
- Several likelihood engines ($\partial a \partial i$, moments, momi2, momentsLD)
- Common interface
- Effective global optimization
GADMA's useful feature:
New Model Specification
GADMA's useful feature:
New Model Specification
New model in GADMA that is specified only by the number of epochs.
Flexible Dynamics
New model in GADMA has flexible dynamics of population size change.
Population dynamic can be:
- Constant
- Linear
- Exponential
Stdpopsim
Stdpopsim
: Easy Data Simulation
Demographic Inference Benchmarking
Demographic Inference Benchmarking
- Simulate datasets using stdpopsim
- Run demographic inference using GADMA
- Use both well-specified and misspecified models
- Benchmark $\partial a \partial i$, moments, momi2, momentsLD
Datasets
Results
Results
We performed a series of experiments for different models and data.
Three the most interesting examples:
-
Well-specified model
-
Misspecified model with flexible dynamics
-
Misspecified models for momi2
Well-specified Model
Well-specified Model
$\partial a \partial i$
moments
momi2
momentsLD
Ground truth: 2,200
Misspecified Model
Misspecified Model
with Flexible Dynamics
moments
momentsLD
Misspecified Models for momi2
Misspecified Models for momi2
Without migration
With 1 pulse event
With 3 pulse events
With 7 pulse events
Conclusions
Conclusions
- Combination of GADMA and stdpopsim is an ideal framework for the demographic inference benchmarking.
- All tested tools perform well for well-specified models.
- Estimations for misspecified models still provide some insights about the studied populations.
Thank you!
Slides: