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rOpenSci - open tools for open science

rOpenSci - open tools for open science
Open Tools and R Packages for Open Science
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babette 1 is a package to work with BEAST2 2 ,a software platform for Bayesian evolutionary analysis from R. babette is a spin-off of my own academic research.As a PhD I work on models of diversification: mathematical descriptionsof how species form new species.

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The United States Deparment of Agriculture National AgriculturalStatistics Service (USDA-NASS) provides a wide range of agriculturaldata that includes animal, crop, demographic, economic, andenvironmental measures across a number of geographies and time periods.This data is available by direct download or queriable via theQuick Stats interface.

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Studies of muscle physiology often rely on closed-source, proprietary software for not only recording data but also for data wrangling and analyses. Although specialized software might be necessary to record data from highly-specialized equipment, data wrangling and analyses should be free from this constraint.

Published
Author Michael Sumner

In May 2019 version 0.2.0 of tidync was approved by rOpenSci and accepted to CRAN. Here we provide a quick overview of the typical workflow with some pseudo-code for the main functions in tidync. This overview is enough to read if you just want to try out the package on your own data.

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Authors Michael Quinn, Elin Waring

Theme song: PSA by Jay-Z We announced the testing version of skimr v2 onJune 19, 2018. After more than ayear of (admittedly intermittent) work, we’re thrilled to be able to say thatthe package is ready to go to CRAN. So, what happened over the last year? Andwhy are we so excited for v2? Wait, what is a “skimr”? skimr is an R package for summarizing your data.

Published

In early September, the version 2.0.0 of rmangal was approved byrOpenSci, four weeks later it made it to CRAN. Following-up on our experience wedetail below the reasons why we wrote rmangal, why we submitted our package torOpenSci and how the peer review improved our package.

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Authors Scott Chamberlain, Brooke Anderson, Anna Krystalli, Lincoln Mullen, Karthik Ram, Noam Ross, Maëlle Salmon, Melina Vidoni

As announced in February, we now have an online book containing all things related to rOpenSci software review. Our goal is to update it approximately quarterly - it’s time to present the third version. You can read the changelog or this blog post to find out what’s new in our dev guide 0.3.0! Updates to our policies and guidance Scope We’ve introduced an important change for anyone thinking of submitting a package.

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The UCSC Xena platform provides an unprecedented resource for public omics data from big projects like The Cancer Genome Atlas (TCGA), however, it is hardfor users to incorporate multiple datasets or data types, integrate the selected data withpopular analysis tools or homebrewed code, and reproduce analysis procedures.

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Teaching collaborative software development In the University of British Columbia’s Master of Data Science program one of the courses we teach is called Collaborative Software Development, DSCI 524. In this course we focus on teaching how to exploit practices from collaborative software development techniques in data scientific workflows.

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Introduction The availability of large quantities of freely available data is revolutionizing the world of ecological research. Open data maximizes the opportunities to perform comparative analyses and meta-analyses. Such synthesis efforts will increasingly exploit “population data”, which we define here as time series of population abundance.