Congratulations to the latest member of the PhD club, Dr. Cathy Viverette! Today, she became the 14th graduate student to graduate from the lab and the very first doctoral student. Take a break, relax, and then let’s get to those revisions! ;-).
A very cool writeup on making blow out maps.
Here are some very useful cheat sheets put out by RStudio. A great resource of information!
I just uploaded a new plugin for RStudio called dlab. I’ll be migrating over all the little helper functions I use to this as a general require() on startup. What it has now is an AddIn that allows you to select text and have it wrapped in the r-code markup. I’m moving stuff between ePub and Markdown and it was needed.
You can install it as:
then look at the AddIns menu for wrapCode.
This may help you understand customizing themes in ggplot much better.
Congratulations to Chitra Seshadri for defending her Masters Thesis entitled, “Genome wide analysis of epigenetic adaptive variance in Araptus attenuatus, the Sonoran Desert bark beetle.” You are #13 graduate student from the Dyer Laboratory (lucky right?).
Here it is, time for student presentations all around! I thought it would be nice to send this presentation around again to remind everyone what make good (and sucky) presentations. More below the fold.
The program STRUCTURE is an ubiquitous feature of many population genetic studies these days—if it is appropriate is another question. Today, while covering model based clustering in population genetics, we ran into a problem where STRUCTURE was unable to run and the OS said it was Corrupted and should be thrown away. Jump below for our fix, it really is an easy one.
An analysis common to modern population genetics is that of finding ecological distances between objects on a landscape. The estimation of pairwise distance derived from spatial data is a computationally intensive thing, one that if you are not careful will bring your laptop to its knees! One way to mitigate this data problem is to use a minimal amount raster area so that the estimation of the underlying distance graph can be done on a smaller set of points. This example provides a simple solution using convex hulls. Jump below for the complete example.
It is often the case that the raster we are working with is not the exact size of the area from which our data are collected. It is a much easier situation if the raster is larger than the area than if you need to stitch together two raster Tiles to get all your data onto one extent. In my doctoral thesis work, the area of the southern Ozark mountains that my sites were in was not only straddling a boundary between existing rasters, it was also at the boundary of two UTM zones! What a pain.
A raster is essentially an image, whose pixel size correspond to a particular spatial extent and the data contained within each pixel represents a particular feature on the landscape. Common rasters are DEM’s (measuring elevation), rainfall, temperature, buildings, etc. In R, it is common to think of rasters as matrices whose values measure some feature on the landscape. In this section, we will examine how to acquire, load, manipulate, and extract data from raster objects.
As part of a collaboration with VDOT, I am pleased to announce that Ms. Bonnie Roderique has just joined the Dyer laboratory to work on a project around the endangered James River Spinymussel (Pleurobema collina). Not a plant, but at least not a vertebrate!
Guess what I get to do?
Another great article, this time on writing style for graduate students, from the Molecular Ecologist.
Here are the slides for the lecture on inbreeding.
I’m giving a seminar at the University of Denver on 22 February about my research program. Here is a link to a PDF version of the talk.
Welcome potential Environmental Studies students
How big is the data set you are analyzing? Apparently it depends on how you count…