The Dyer Laboratory: Population Graphs Swift Edition

Rodney Dyer

So this spring, I’m going to make a large push at porting over the population graphs analyses (Dyer & Nason 2004) that I have in R to a version that runs as a native app on iOS/MacOS. The long-term goals here are to leverage the upcoming advances in Augmented Reality and LiDAR at the phone/glasses level that I suspect will be more mainstream by 2023 or so.

Big Picture

So, in the long run, I’m looking to have a set of software that can do the following:

Estimate a population graph from genotype data.
- Write custom SVD routines linked with Accelerate.
- Wrap in GeneticStudio interface for Genotype & Project CRUD.
Visualize the graph in either 2D (SpriteKit), 3D (SceneKit), or in AR (ARKit).
- Force directed estimation of location in 2-space
- Expand to 3-space
- Develop individual physics models for dynamical system in SpriteKit & SceneKit
Comprehensive set of network-based analytical output for local (node- and edge- centric) as well as global parameters.
Overlay spatial network on GeoTiff for prevalence/avoidance of features.
Chromosome walking - Use engine to analyze how population covariance changes along stretches of chromosomes from SNP-like data.
Population Simulation - Develop stochastic simulation background that is visualized using dynamical population graphs for hypothesis testing, where we specify a model and

Citation

For attribution, please cite this work as

Dyer (2021, March 3). The Dyer Laboratory: Population Graphs Swift Edition. Retrieved from https://dyerlab.github.io/DLabWebsite/posts/2021-03-03-population-graphs-swift-edition/

BibTeX citation

@misc{dyer2021population,
  author = {Dyer, Rodney},
  title = {The Dyer Laboratory: Population Graphs Swift Edition},
  url = {https://dyerlab.github.io/DLabWebsite/posts/2021-03-03-population-graphs-swift-edition/},
  year = {2021}
}