The R Shiny application is now running on shinyapps.io. You don’t need to worry about the local installation instructions I provided on the 27th (unless you’d prefer to run it locally, in which case you should probably just clone the whole Git repository).
I just updated notes on AMOVA, statistical phylogeography, and population genomics. There will be an R Shiny application on shinyapps.io (I hope). It’s the one I referred to on the 27th. It’s written and it runs on my computer (it will run on yours if you download it and follow the instructions). I’m working with R Studio support to sort out the problem, and I hope it will be fixed before long.
I’ve updated my notes on molecular evolution. You can find them in three ways:
- From the Lecture notes page
- From the detail page associated with each lecture in the Lecture schedule
- From this list
Next up: AMOVA and statistical phylogeography
I just posted another R Shiny application illustrating properties of the coalescent in two populations with mutation and migration. Unfortunately, to see this one, you’ll have to download the source from Github (app.R) and run it in your local version of R. It’s not difficult, but it’s less convenient than running it on shinyapps.io. The problem arises because I use ggtree() to plot and color the tree. ggtree() is a BioConductor package, and I’m running into an error installing it in the application package. If I can’t figure it out, I may install a version of R Studio Server here and host it locally.
Here’s how to run the application in your local version of R:
- Follow the link to Github and download app.R (click on the button labeled “Raw” at the right side of the screen and use “File->Save” to save it somewhere convenient on your hard drive.
- Make sure your version of R has the libraries mentioned at the top of app.R installed. They are: ggplot2, shiny, cowplot, plotly, coala, ggtree, and ape. (Actually, I think you can delete cowplot and plotly from the list of libraries that are loaded. They’re leftover from some earlier experiments. To install ggtree(), you’ll first have to make sure that you have BiocManager installed. Then you can simply BiocManager::install("ggtree").
- Launch R and make sure your working directory contains the source for app.R.
- Then runApp() and enjoy the ride!
Yes, I know it’s December 23rd and that it’s not only Sunday, but also only two days before Christmas. Even so, I spent the afternoon revising notes on the coalescent process and developing an R Shiny application to illustrate the genealogical properties of the coalescent. If you’re reading this, please consider them a small holiday gift from me.
I’ve updated notes on the interaction of genetic drift with mutation, and to complement the notes, I’ve written a new simulation in R Shiny and Plotly to illustrate both the dynamics of allele frequency changes within populations and the distribution of allele frequencies among populations. I’ve also updated notes on the interaction of genetic drift and natural selection. I’m having some kind of a weird permission problem with my server. A copy of the PDF that I just linked to with the original name (selection-drift.pdf) and the same permissions (at least so far as I can tell) keeps giving me a permission error when I try to download it. I’ll leave temp.pdf on the server, but I hope to fix the permission problem, so it would be best not to link to that file until I get it fixed.
I’ve posted the last set of notes on selection, outlining the principles of estimating viability components of fitness from observations on genotypes before and after selection. I’ve also posted notes on basic principles of genetic drift, including the concept of effective population size. In addition, I’ve written an application in R Shiny that lets you explore the properties of genetic drift. You can pick the initial allele frequency, the number of different populations subject to drift (from one to ten), the (effective) population size of each population, and the number of generations for the simulation to run.
I’ve posted notes on viability selection at one locus with two alleles: http://darwin.eeb.uconn.edu/eeb348-notes/selection.pdf. I also wrote and posted a simply R Shiny application that allows you to see the within-generation effect of viability selection using a fixed set of genotypes and sliders to pick viabilities: https://keholsinger.shinyapps.io/Viability-selection/. Enjoy!