This post is the 1st post of a series showcasing various rOpenScipackages as if Maëlle were a birder trying to make the most of R ingeneral and rOpenSci in particular. Although the series use cases willmostly feature birds , it’ll be the occasion to highlight rOpenSci’spackages that are more widely applicable, so read on no matter what yourfield is! Moreoever, each post should stand on its own.
This week version 2.0 of the mongolite package has been released to CRAN. Major new features in this release include support for MongoDB 4.0, GridFS, running database commands, and connection pooling. Mongolite is primarily an easy-to-use client to get data in and out of MongoDB. However it supports increasingly many advanced features like aggregation, indexing, map-reduce, streaming, encryption, and enterprise authentication.
In this technote I will outline what phylotaR was developed for, how to install it and how to run it with some simple examples. What is phylotaR? In any phylogenetic analysis it is important to identify sequences that share the same orthology – homologous sequences separated by speciation events. This is often performed by simply searching an online sequence repository using sequence labels.
eBird is an online tool for recording birdobservations. The eBird database currently contains over 500 millionrecords of bird sightings, spanning every country and nearly every birdspecies, making it an extremely valuable resource for bird research andconservation. These data can be used to map the distribution andabundance of species, and assess how species’ ranges are changing overtime. This dataset is available for download as a text file;
Motivation A few weeks ago, as part of the rOpenSci Unconference, a group of us (Sean Hughes, Malisa Smith, Angela Li, Ju Kim, and Ted Laderas) decided to work on making the UMAP algorithm accessible within R. UMAP (Uniform Manifold Approximation and Projection) is a dimensionality reduction technique that allows the user to reduce high dimensional data (multiple columns) into a smaller number of columns for visualization purposes (github,
tl;dr : we propose three calls to action: Share your curricular materials in the open. Participate in the rOpenSci Education profile series. Discuss with us how you want to be involved in rOpenSci Educators’ Collaborative.
In the first post of this series, we sketched out some of the common challenges faced by educators who teach with R across scientific domains. In this post, we delve into what makes a “good” educational resource for teaching science with R. For instructors teaching sciences with R, there are a number of open educational resources that they can reuse, tailor to their own teaching style, or use to inspire them in creating their own materials.
Educators who teach science using R tend to face common pedagogical problems, regardless of their scientific domain. Yet instructors who teach with R often feel isolated at their institutions. They may be the only ones in their departments to teach using R. Even if there are others, the culture of collaboration around teaching is generally impoverished, unlike the rich culture of collaboration around research.
The gifski package which was demonstrated in May at eRum 2018 in Budapest is now on CRAN. Gifski is a simple but powerful package which can hopefully take away an important performance bottleneck for generating animated graphics in R. What is Gifski Gifski is a multi-threaded high-quality GIF encoder written in Rust. It can create animated GIF images with thousands of colors per frame and do so much faster than other software.
R packages are widely used in science, yet the code behind them often does not come under scrutiny. To address this lack, rOpenSci has been a pioneer in developing a peer review process for R packages. The goal of pkginspector is to help that process by providing a means to better understand the internal structure of R packages.
