A quick introduction to ggplot2
My friend Jonah asked me to guest lecture in his R seminar aimed at grad students and postdocs in Integrative Biology. I gave Jonah a bunch of topic options ranging from reproducible research with R to data manipulation. The consensus was data visualization so I put together a 2 hour talk/hands on presentation for ggplot2 […] Read more – ‘A quick introduction to ggplot2’.
An intro to R
A few weeks back I gave a talk at the local Berkeley R meetup group. The idea was to help people not make the same mistakes I made when I first started out learning R. It was the first time I made an entire presentation with Deck.js and I generated the syntax highlighted R code […] Read more – ‘An intro to R’.
Two incredibly useful functions to throw into your .rprofile
I’ve neglected this blog for quite some time but I’m getting around to finishing up a bunch of draft posts. But here is a quick one: Listing objects in your global environment A simple ls() doesn’t really tell you enough useful information at a glance. Most often I just want to know what I named […] Read more – ‘Two incredibly useful functions to throw into your .rprofile’.
Customizing your .rprofile
I searched around to see if there was a blog post somewhere describing how to customize one’s .rprofile but was surprised to find just one outdated post. So here is quick intro on the topic. If you are a power R user, you already know about what it does. For those of you that don’t, […] Read more – ‘Customizing your .rprofile’.
HPC for biological research
In early May I had the opportunity to attend a workshop on using high performance computing in R hosted at Nimbios. I’ve been meaning to write a summary of the meeting ever since but got sidetracked by various other projects. Since a collaborator recently asked for meeting notes I finally took the time to write […] Read more – ‘HPC for biological research’.
Climate datasets in R
As an ecologist working on climate change questions, I’ve always found it rather tedious to acquire and process climate data, especially when dealing with large spatiotemporal scales. Although many agencies provide free access to climate data, there is often some overhead (typically one to two days) before the data are made available for download via […] Read more – ‘Climate datasets in R’.
R + EC2 + RStudio Server
I’ve been battling memory limits in R for over two years. Although R has numerous resources for high-performance computing, I still couldn’t get around hardware limitations. Things really got out of control last summer when I started analyzing data on how climate change influences population synchrony across large spatiotemporal gradients. My datasets were simply too […] Read more – ‘R + EC2 + RStudio Server’.
Staying up to date on R packages
Unless you regularly use particular R packages,  it’s becomes difficult to stay on top of updates and bug fixes.  Updates usually also include significant improvements in performance.  I wrote this short snippet of code which I run about once a month to keep up on updates. Read more – ‘Staying up to date on R packages’.