Generating reasonable starting trees for complex phylogenetic analyses
I never really thought I would write an R package. I use R pretty casually. Then, this year, I was invited to participate during the last week of the Analytical Paleobiology short course, an intensive month-long experience in quantitative paleontology. I was thrilled to be invited. But I got a slight sinking feeling in my stomach when I realized all the materials were in R. And so I, a Pythonista, decided I would spend some of my maternity leave writing R packages to try to blend in with students who had spent the month living and breathing R.
Community Call - Governance strategies for open source research software projects
🎤 Dan Sholler, rOpenSci Postdoctoral Fellow 🕘 Tuesday, December 18, 2018, 10-11AM PST; 7-8PM CET (find your timezone) ☎️ Details for joining the Community Call. Everyone is welcome. No RSVP needed. Researchers use open source software for the capabilities it provides, such as streamlined data access and analysis and interoperability with other pieces of the scientific computing ecosystem. For most complex software, generating these technical capabilities requires building and governing a community via sound management practices, activities that are often less visible than code contributions and other software development work.
Detecting spatiotemporal groups in relocation data with spatsoc
spatsoc is an R package written by Alec Robitaille, Quinn Webber and Eric Vander Wal of the Wildlife Evolutionary Ecology Lab (WEEL) at Memorial University of Newfoundland. It is the lab’s first R package and was recently accepted through the rOpenSci onboarding process with a big thanks to reviewers Priscilla Minotti and Filipe Teixeira, and editor Lincoln Mullen. spatsoc started as a single function (what would eventually become group_pts) written by Alec in 2017 to help answer some of the questions that Quinn and Eric were asking about how animal social structure is related to spatial processes.
Community Call Summary - Code Review in the Lab
Although there are increasing incentives and pressures for researchers to share code (even for projects that are not essentially computational), practices vary widely and standards are mostly non-existent. The practice of reviewing code then falls to researchers and research groups before publication. With that in mind, rOpenSci hosted a discussion thread and a community call to bring together different researchers for a conversation about current practices, and challenges in reviewing code in the lab.
Co-localization analysis of fluorescence microscopy images
A few months ago, I wasn’t sure what to expect when looking at fluorescence microscopy images in published papers. I looked at the accompanying graph to understand the data or the point the authors were trying to make. Often, the graph represents one or more measures of the so-called co-localization, but I couldn’t figure out how to interpret them. It turned out; reading the images is simple. Cells are simultaneously stained by two dyes (say, red and green) for two different proteins.
