Automated gene to spatiotemporal observation associator.
I noticed that the ALA had several species with associated genomic data. These species also had associated observation data, with coordinates and dates.
By grouping closely related genes, and binning observations into spatiotemporal variation of some resolution, we can observe the movement and clustering of genes rather than individual species. Among other things, this may lead to insights as to the genetic factors behind biodiversity loss and climate change driven migration events.
The main issue with this project is the critical assumptions behind any findings. While most of these assumptions are violated in the primary intended dataset, the pipeline is intended to be a proof of concept for use with more accurate and better curated datasets.
- Observations of species are not misclassified
- Observations of species occur uniformly relative to their true population
- Species have negligible genetic variation over observation range