Introduzione al Corso

Introduzione all’analisi RNASeq in R

Dipartimento di Biomedicina e Prevenzione



Marco Chiapello, Revelo Datalab

2023-03-31

Code of Conduct

We are dedicated to providing a welcoming and supportive environment for all people, regardless of background or identity.

By participating in this course, participants accept the Code of Conduct.

Any form of behaviour to exclude, intimidate, or cause discomfort is a violation of the Code of Conduct. In order to foster a positive and professional learning environment we encourage the following kinds of behaviours in all platforms and events:

  • Use welcoming and inclusive language
  • Be respectful of different viewpoints and experiences
  • Gracefully accept constructive criticism
  • Focus on what is best for the community
  • Show courtesy and respect towards other community members

Presentiamoci

Chi sei?


Cosa hai studiato?


Quali sono i tuoi obiettivi?


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Com’è strutturato il corso

Website

http://bit.ly/3ZcDcj9

Agenda

Primo Giorno Teoria


Orari
9:30 : Introduzione al Corso
10:00: Riepilogo R
10:45: Pausa
11:00: Introduzione all’RNASeq

12:30: Pausa pranzo

13:30: Ricerca Riproducibile
14:45: Pausa
15:00: Software and code
16:30: Considerazioni finali

Secondo Giorno Pratica


Orari
9:30 : Live Code (QC and quantification)
10:45: Pausa
11:00: Live Code (DGE)

12:30: Pausa pranzo

13:30: Live Code (DGE)
14:45: Pausa
15:00: Capstone exercise
16:30: Considerazioni finali

Teaching system

Approach

  1. Open source tools

  2. Supporting community

  3. Your laptop is everything you need

  4. Constant feedback

  5. Ask questions

Feedbacks

  • Immediati

    • Sticky notes

  • Formative assessment

    • Veloci questionari o esercizi

  • Alla fine di ogni modulo

    • Sticky notes

Domande



Don Lorenzo Milani

Ogni parola che non capisci oggi è un calcio in culo domani

Strumenti

  • Website

  • Slack

    • Strumento di comunicazione



Entrambi rimarranno online per sempre

Goals

Goals

  1. Become a better data scientist
  1. Leanr best practices for working with R/Bioconductor
  1. Understand how to do RNASeq bulk data analysis
  1. Develop a lightweight and reusable RNASeq pipeline

Domande?

Tutto

in questo corso

è stato fatto in R

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