Introduzione a R per la manipolazione efficace di dati (Intro2R)

  • 1. Intro2R Infobiology course

    Here you can find the most updated program of the course. Slight modifications can be made without notice: if you have a static (i.e. printed or pdf) version of the program, refer to this online version as the most updated.

  • 2. A gentle introduction

    Introductory and background material on the R environment, course aim, and some data concepts and theory.

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  • 3. Prepare your computer

    Instructions on how to install and approach the software you will need.

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  • 4. Basic R syntax

    The very first basic "how tos" in R

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  • 5. Interactive tutorials

    R methods and data structures: online and offline intractive tutorials

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  • 6. Material used and Resources

    This section contains the files (datasets, scripts and tutorials) that you will need to download during the live course

Programma Corso Intro2R

“Introduzione alla manipolazione dei dati con R” (Intro2R)

2 weeks online program

(To be carried on autonomously on your laptop accessing the dedicated account on our online platform. Approximate time needed to complete the online tasks: from 4 to 8 hours TOTAL, depending on skills)

1) A gentle introduction

  • What is R and R environment, R learning
  • R versus Excel
  • Tidy data and the Tidyverse

2) Prepare your computer

  • “R” and “RStudio” installation
  • The R Console

3) The basics

  • Basic R operations
  • The R packages and Repositories
  • Swirl interactive tutorials
  • TryR-CodeSchool interactive tutorials


2-days live course program (in Pero, Milan)

(Each participant needs to bring her/his own laptop. Coffee breaks and light lunches will be served directly at the venue for both days)

Day 1

9.30 am Registrations (those who encountered serious problems during software installations on own laptops, please arrive by 9.00 am in order to have the proper assistance)

Morning Session 10.00 – 13.00

0) Introduction

  • Technical check on personal laptops
  • Welcome address and quick mutual presentations
  • Your path to data freedom. What to expect, what to aim for.

1) The data science environment

  • The grammar of Data Science
  • Why and how to talk to a computer
  • Structure of a command. Functions, attributes

2) The R universe

  • Using the R console with RGUI and RStudio
  • The R syntax. A very quick remind of previous 2 weeks.
  • Objects (and “object oriented”) and evaluation. Data structures.
  • Read data into R. A first practical dataset

Afternoon Session 14.00 – 17.30

4) Tidy and manipulate your data

  • The “Tidyverse” vs base syntax
  • Tools for tidiness: piping commands, summarizing, filtering, merging

5) Annotations DBs

  • Matrices and dataframes
  • Enrich your data with annotations: the biomaRt package


Morning Session 9.30 – 12.30

6) Wrap-up and previous day summary

  • What did you learn yesterday? Q&A session

7) Automation and iteration

  • Concepts of control flow
  • “for” loops
  • Conditionals “if-else”

8) Basic data visualizations

  • Basic plotting with R
  • Introducing ggplot2
  • Customize your graphics.
  • Leverage data-viz with ggplot and geom levels

Afternoon Session 13.30 – 16.30

9) Quick info on reproducibility and documenting with R

  • R Markdown and R notebooks
  • Reports with R

10) Packages for biological analyses

  • Overview of selected packages
  • Other things you may encounter: the tibble, the data.table

11) Practical take-home messages

  • How to keep learning from here
  • Where to go to consolidate your skills
  • What to do to jump start your skills