I’ve been using a custom library for R since 2012 and I’ve never looked back. I’ve not seen many tutorials for people do do this through R, so I figured I’d write a quick one. Where does your R package library live? You can usually find this out by typing .libPaths() in your R console. If you have an out-of-the-box installation, it will generally be somewhere like: C:/Program Files/R/R-3.
A couple of weeks ago, I wanted to explore assembling 55 genomes of Sclerotinia sclerotiorum to check for structural rearrangements that could be caused by sub-lethal fungicide exposure. I figured the best way to do this was to assemble these genomes de novo as opposed to aligning them to a reference. This brought me to installing the ABySS de novo assembler on the HCC Tusker Cluster… and I can happily report, that after half a day of [command line bullshittery]1, I had ABySS up and running 👍.
Today, we finally published a preprint for a manuscript that spans over 15 years of data 🎉! Our massive Sclerotinia pop gen study out as preprint today @PeerJPreprints https://t.co/O85hUURi2s #AgriculturalScience #Genetics #Mycology — Dr. Sydney Everhart (@SydneyEverhart) October 3, 2017 Here’s the citation: Kamvar ZN, Amaradasa BS, Jhala R, McCoy S, Steadman JR, Everhart SE. (2017) Population structure and phenotypic variation of Sclerotinia sclerotiorum from dry bean in the United States.
As I was preparing to push a new version of poppr to CRAN , this tweet (appropriately) came across my feed: Mistakes happen in science. What matters is what you do next. Anyone want to share a story of a mistake & how they handled it? — Adriana Porter Felt (@apf) September 10, 2017 The reason I was updating poppr was to fix a mistake I had made a few years ago.
My R package poppr hit over 20,000 downloads on CRAN. I thought this would be a nice opportunity to briefly talk about what initiated the development. Before that, let’s look at the cumulative number of downloads: CRAN you dig it? Thanks to the fantastic cranlogs package, assessing the download history of a package is quite simple (with the caveat that these are logs from the rstudio mirror, so the value is almost always lower than the true value).