Course Introduction

Prerequisites

Participants must be able to use a laptop/computer capable of running recent RStudio. See below for the RStudio Installation section.

Teachers

Szymon M. Kiełbasa (s.m.kielbasa@lumc.nl)
Ramin Monajemi (r.monajemi@lumc.nl)
Mo Arkani (m.arkani@lumc.nl)

What we teach

R is an open-source, free environment/language for statistical computing and graphics. It provides a large repository of statistical analysis methods.

The goal of the course is to teach you how the R language, extended by tidyverse package, can be used to build a report with a simple statistical analysis of data provided in a table. The course assumes no prior programming knowledge.

NOTE: This is not a statistics course! We do not teach statistics; we teach how to write simple programs in the R language. Elementary statistics knowledge is necessary to understand examples.

After the course you will:

Read and write (tidyverse-based) R code.
Know where to look for R methods to perform statistical analyses of your own data.
Generate reproducible reports from your own data in HTML, PDF or DOC formats.

We will cover the following topics:

R expressions.
R data objects: vectors, data frames (tibbles), lists, (matrices).
R Markdown for building reproducible reports.
Data manipulation: filtering, sorting, summarising of a table; joining/merging multiple tables (with tidyverse/dplyr and tidyverse/tidyr).
Visualisation: scatter plots, histograms, boxplots (with tidyverse/ggplot2).
R packages: installation and usage.

Course structure

The course takes up 4 days and is divided in 8 half-day sessions. The first and the last days sessions will take place in the lecture hall 3 (LUMC main building) and days 2 and 3 on an online plenary room (ZOOM). The interaction with teachers in the online session is possible via the ZOOM chat line.

All sessions: practicing

Each session is split into a few small topics and each topic is introduced as follows:

A short lecture for introduction/demonstration.
Followed by a practical (with primary exercises end extra exercises).

The students are asked to type on their keyboards the commands being presented and observe effects (avoid copy-paste; own typing is important in order to learn how to respond to mistakes/errors).

The last session: practicing followed by self study assignment

A self study assignment (SSA) will be offered during the last session. A set of tasks will be provided to you to be solved without help of the teachers or others. At the end there will be a Q/A for general discussion.

The overall SSA goal is to prepare an R Markdown document reporting an analysis of a dataset. You will be asked to carry out the following steps:

Create an RStudio project, knit an R Markdown document.
Read a provided table.
Show some filtered/summarized content of the table.
Produce some plots of the data.

Installation

Installation of R and RStudio software, including additional packages, is required before the start of the course. Please follow the instructions below.

NOTE: Resolving installation problems during the course may be impossible, therefore please follow the steps below a week before the start of the course. In case of failure, please inform the teachers. In some situations intervention of the administrator of your computer might be necessary.

Install R: go to the R Project for Statistical Computing (https://www.r-project.org/) and follow the download and installation instructions.
Install RStudio: go to the RStudio download page (https://www.rstudio.com/products/rstudio/download/#download), select a version of RStudio appropriate for your laptop, download it and then install. Please check whether you can start RStudio.
CAUTION LUMC Windows users: Installation of the R software via the LUMC Software Center is strongly recommended (instead of via the R websites above). This should avoid the following problem: Programs, such as R and RStudio may be installed on LUMC network drives instead of local drive ‘C:’. In that case some functionalities may fail, in particular generation of R Markdown reports. A solution is to force the installation on your local drive such as ‘C:’, this however, may require administrator privileges which you may not have. Alternatively you may consider a separate laptop which is not administered on LUMC network for the time being and try to resolve the issue later with your system administrator.

Some additional packages are needed for the course. During the course the participants will learn how to install packages but this process occasionally fails (because e.g.: additional steps are needed in a particular operating system, or there is lack of permissions to access some system directories, or other software is too old, …).

Install tidyverse package: Start RStudio. Go to menu Tools/Install Packages… In the field Packages select tidyverse. Press Install. (Now, a lot of messages will be shown in the Console window - wait till it finishes). In the Console window type library( tidyverse ) and press Enter. Some messages might be displayed but when there is no error the installation is completed.
Install packages needed for R Markdown: Start RStudio. Go to menu File/New File/R markdown…. A New R Markdown window is displayed. Press OK. Now, in case of missing R Markdown packages, you will be asked to install them. Finally, you will see an editor window with Untitled1 header. Put the cursor in that window, then click Knit. Some messages might be displayed but when later a window with some text and a plot is shown the installation is completed. During the course applications in multiple windows will be used. For better experience we advice a setup with two monitors (e.g. laptop and an external monitor).

R Introduction →