CEX2018-000792-M

Introduction to R

Duration: 8 hours / 2 days

Date: 7th and 9th of November 

Time: 9:30 - 14:00 

Format: Presential.  Dr. Aiguader 80, Barcelona - classroom 61.212 (2nd Floor - teaching building)

Available places: 15

Course Description

Introduction to R programming language for statistical analysis and visualization. We will explore some CRAN basic packages, as well as Bioconductor packages useful for Biomedical applications. We will explore R variables, data types and structures, functions, statistics and graphical representations. In addition, we will learn how to use RStudio, an integrated development environment (IDE) for R.

The aim of this course is to introduce the R language and give hands-on experiences on how to use it.  

Why should you attend the course?

R is an open-source statistical computing language adequate for data analysis in many disciplines. This course provides a basic understanding of how to use R and for which applications this can be used. The achieved skills will enable you to manage with confidence and efficiently your data. After this introductory course, you will be able to handle, analyze and visualize different kinds of data. Graphical visualizations will have enough quality to be used for public presentations such as posters, presentations or article figures. 

Prerequisites

This course has no formal prerequisites. 

You should bring your own laptop with R and Rstudio installed. There will also be some packages to install before the course. 

Finally, clone the bitbucket repository with the course materials before the lessons. 

Schedule

Day 1

• Introduction to R objects (reading/writing data, basic objects)
• Introduction to RStudio 
• Data cleaning, merging, types of data
• R functions

Day 2

• Data visualization
• Statistical analysis 
• Application examples

Class Pace 

We encourage the participants to do as many questions as needed during the whole course. The hands-on practical session aims to enhance dynamic learning.  

References

•  Leeper, Thomas. 2016. Really Introductory Introduction to R.
• Grolemund, Garrett and Hadley Wickham. 2017. R for Data Science. O'Reilly.
• Hadley Wickham, Danielle Navarro, and Thomas Lin Pedersen. 2020. ggplot2: elegant graphics for data analysis. Springer.

Short biography 

Marta Sanvicente is a PhD candidate in the Translational Synthetic Biology laboratory at Universitat Pompeu Fabra. Previously, she did the Master in Bioinformatics for Health Sciences at Universitat Pompeu Fabra (2017-2019) and Bachelor’s degree in Genetics at Universitat Autònoma de Barcelona (2013-2017). Her research interests include Next Generation Sequencing data analysis, nextflow pipelines development, and analysis, simulation and prediction of genome editing and gene writing outcomes. 

MELIS-UPF is a “Unidad de Excelencia María de Maeztu”, funded by the MCIN and the AEI (DOI: 10.13039/501100011033). Ref: CEX2018-000792-M