Ashbya is a filamentous fungus and a pretty close relative of the brewer's yeast and all-star model organism Saccharomyces cerevisiae. Although Ashbya is itself a pretty popular model organism, only a couple of genomes are publicly available, and we still don't know too much about its populations in nature. Here I am using new whole-genome sequencing data to look at population structure in Ashbya isolated from insect and plant hosts. This is a work in progess.
The source data for this project inlcudes a variant call file (VCF) and a metadata file. The VCF lists the differences between the Ashbya gossypii reference genome and sequencing reads that were aligned to it. I have reason to believe that many of these isolates are actually closely related, non-gossypii species, which I hope to address in the future. The metadata file is included in this repo but the VCF is very large and will be downloaded from a remote host when the Makefile is run. This may take a while (~5 minutes).
First you need to clone this repository.
Use the terminal to navigate to where you would like to make a copy of this repository and type or paste git clone https://github.com/crockeraw/ashbya-genomes-pop-gen.git. To actually run the scripts to reproduce the analysis you will need to have Docker installed on your computer, or manually install of the dependencies (not yet listed).
The easiest and quickest way to build and interact with this project is by running the provided bash script (in a linux/mac terminal) by navigating to the project directory and typing sudo bash start-rstudio.sh <custom-password> and navigating to localhost:8787 in a web browser. Your username will be rstudio and password will be the custom password you provided, or "foo" if none was given.
If you do not want to create an Rstudio session you can simply run:
sudo docker build . -t ashyba
sudo docker run -it ashbya
This project consists of images, datasets, and the R scripts that generate them; as well as an html report summarizing all findings, and a shiny app to explore them.
To build the entire project run the command make. This can be run in a terminal either in the Rstudio session accessed through the browser, or through an interative Docker session. To view the report simply open the file derived_data/report.html in your browser.
If you would like to run a shiny-app to visualize some aspects of the population structure you can launch it though the R console by typing library(shiny); runApp(shinyapp) in R, or you can access the app online here: https://alex-crocker.shinyapps.io/ashyba-pop-gen/?_ga=2.72639898.826599290.1641249641-868820857.1639163203