Three presentations uploaded on LondonR meetings website. I especially enjoyed the JD Long presentation on the seque package for simulations using Amazon’s EC2.

I am part of the rOpenSci development team (along with Carl Boettiger, Karthik Ram, and Nick Fabina). Our website: http://ropensci.org/. Code at Github: https://github.com/ropensci We entered two of our R packages for integrating with PLoS Journals (rplos) and Mendeley (RMendeley) in the Mendeley-PLoS Binary Battle. Get them at GitHub (rplos; RMendeley). These two packages allow users (from R! of course) to search and retrieve data from PLoS journals (including their altmetrics data), and from Mendeley. You could surely mash up data from both PLoS and Mendeley. That’s what’s cool about rOpenSci - we provide the tools, and leave it up to users vast creativity to do awesome things. 3rd place gives us a $1,000 prize, plus a Parrot AR Drone helicopter. ...

See http://www.surveygizmo.com/s3/722753/Mendeley-PLoS-Binary-Battle-Public-Vote

I gave a talk today on doing very basic phylogenetics in R, including getting sequence data, aligning sequence data, plotting trees, doing trait evolution stuff, etc. Please comment if you have code for doing bayesian phylogenetic inference in R. I know phyloch has function mrbayes, but can’t get it to work… Phylogenetics in R View more presentations from schamber

Okay, so this post isn’t at all about R - but I can’t resist begging my readers for some help. I’m trying to get some crowdfunding for my research on the evolution of native plants in agricultural landscapes. My campaign is part of a larger project by about 50 other scientists and me to see how well it works to go straight to the public to get funding for science research. All these projects, including mine, are hosted at a site called RocketHub - a site that hosts crowdfunding projects of all sorts – and now they have science. ...

With examples from rOpenSci R packages. p.s. I am no expert at this... Web data from R View more presentations from schamber

Carl Boettiger, a graduate student at UC Davis, just got two packages on CRAN. One is treebase, which which handshakes with the Treebase API. The other is rfishbase, which connects with the Fishbase, although I believe just scrapes XML content as there is no API. See development on GitHub for treebase here, and for rfishbase here. Carl has some tutorials on treebase and rfishbase at his website here, and we have an official rOpenSci tutorial for treebase here. Basically, these two R packages let you search and pull down data from Treebase and Fishbase - pretty awesome. This improves workflow, and puts your data search and acquisition component into your code, instead of being a bunch of mouse clicks in a browser. ...

Tom Miller (a prof here at Rice) and Brian Inouye have a paper out in Ecology (paper, appendices) that confronts two-sex models of dispersal with empirical data. They conducted the first confrontation of two-sex demographic models with empirical data on lab populations of bean beetles Callosobruchus. Their R code for the modeling work is available at Ecological Archives (link here). Here is a figure made from running the five blocks of code in ‘Miller_and_Inouye_figures.txt’ that reproduces Fig. 4 (A-E) in their Ecology paper (p = proportion female, Nt = density). Nice! ...

So, there is a new food web dataset out that was put in Ecological Archives here, and I thought I would play with it. The food web is from Otago Harbour, an intertidal mudflat ecosystem in New Zealand. The web contains 180 nodes, with 1,924 links. Fun stuff… igraph, default layout plot igraph, circle layout plot, nice My funky little gggraph function plotget the gggraph function, and make it better, here at Github

So, I’ve blogged about this topic before, way back on 5 Jan this year. Matt Helmus, a postdoc in the Wootton lab at the University of Chicago, published a paper with Anthony Ives in Ecological Monographs this year (abstract here). The paper addressed a new statistical approach to phylogenetic community structure. As I said in the original post, part of the power of the PGLMM (phylogenetic generalized linear mixed models) approach is that you don’t have to conduct quite so many separate statistical tests as with the previous null model/randomization approach. ...