This week, the useR!2017 conference took place in Brussels. useR! is the annual international R User conference and is the main meeting of the R user and developer community. More than 1,000 people from all over the world came to Brussels to discov...

R 3.4.1 (codename “Single Candle”) was released several days ago. You can get the latest binaries version from here. (or the .tar.gz source code from here). As mentioned last week by David Smith, R 3.4.1 includes several Windows related bug fixed: including an issue sometimes encountered when attempting to install packages ...

I’ll be running a training course in a few weeks which will use RStudio as the main computational tool. Since it’s a short course I don’t want to spend a lot of time sorting out technical issues. And with multiple operating systems (and versions) these issues can ...

For many R users the magrittr pipe is a popular way to arrange computation and famously part of the tidyverse. The tidyverse itself is a rapidly evolving centrally controlled package collection. The tidyverse authors publicly appear to be interested in re-basing the tidyverse in terms of their new rlang/tidyeval ...

Shiny is an R Package to deploy web apps using an R backend. Let’s face it, Shiny is awesome! It brings all the power of R to a simple web app with interactivity, user inputs, and interactive visualizations. If you don’t know Shiny yet, you can access a ...

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By Thoralf Mildenberger (ZHAW) Everybody who knows a bit about R knows that in general loops are said to be evil and should be avoided, both for efficiency reasons and code readability, although one could argue about both. The usual … Continue reading →

Assessing the accuracy of our model There are several ways to check the accuracy of our models, some are printed directly in R within the summary output, others are just as easy to calculate with specific functions. R-Squared This is probably the most commonly used statistics and allows us to ...

This post was originally part of my previous post about linear models. However, I later decided to split it into several texts because it was effectively too long and complex to navigate.If you struggle to follow the code in this page please refer to this post (for example for ...

After publishing my previous post, I realized that it was way too long and so I decided to split it in 2-3 parts. If you think something is missing in the explanation here it may be related to the fact that this was originally part of the previous post (http://...

Simulation can be super helpful for estimating power or sample size requirements when the study design is complex. This approach has some advantages over an analytic one (i.e. one based on a formula), particularly the flexibility it affords in setting up the specific assumptions in the planned study, such ...

Genetics is a data science, right? One of my Summer of data science learning points was to play with out of the box prediction tools. So let’s try out a few genomic prediction methods. The code is on GitHub, and the simulated data are on Figshare. Genomic selection is ...