OLISSIPO Workshops | EMBL Trainings in Computational Biology
The EMBL team, one of the partner institutions of the OLISSIPO project, will visit INESC-ID to give a series of workshops in the area of Computational Biology. You are free to choose the workshops you want to attend (only Workshop 2 requires the attendance of Workshop 1).
Location: INESC-ID (Lisboa, Portugal), Room 9, Floor -1 (ask at the reception)
Workshop 1 (WS1) (May 9, 09:00-16:00)
Title: Introduction to R
Lecturer: Mike Smith
This one day course provides an introduction to data handling with the R language and will cover some useful tools for data wrangling, exploration and plotting using the tidyverse. The course material is suitable for beginners, although basic familiarity with R will be advantageous.
Prerequisites: A working installation of R and RStudio. Installation instructions for both can be found under “Setup Instruction” on https://grp-bio-it-workshops.embl-community.io/introduction-to-R/index.html
Workshop 2 (WS2) (May 10-11, 09:00-13:00)
To attend this course it is necessary to attend Workshop 1
Title: Biostatistical Basics in R
Lecturer: Sarah Kaspar
This course will equip you with basic statistical concepts that will immediately help you to better understand your biological data, and which are also the foundation for many advanced biostatistical topics.
We will cover:
- statistical distributions
- hypothesis testing
- multiple testing
- contingency tables
Prerequisites: You need to have R and RStudio installed, and basic knowledge of R and data visualisation using the tidyverse. If you don’t have this pre-knowledge you can complete one of the following:
- Tuesday’s “Introduction to R” course
- The carpentries Introduction to R (working on your local RStudio)
- The EMBL-EBI tutorial on data handling and visualisation in R (working in the browser)
Workshop 3 (WS3) (May 10, 14:00-18:00)
Title: Drug Synergy
Lecturer: Petr Smirnov
This workshop introduces the fundamental concepts behind analysing drug combination experiments on immortalised cancer cell lines; discusses common models for assessing drug synergy, and introduces R/Bioconductor tools implementing these methods. A hands on analysing public drug combination data is included.
The learning goals behind this workshop are:
- Describe pharmacogenomic mono and combination datasets and usefulness in cancer research
- Understand how experimental designs and research questions map onto data structures
- Learn how to extract information from these datasets
- Learn how to visualise experimental results from these datasets
- Learn how to model dose-response for both monotherapy and combination small compound datasets
- Learn measures to quantify response and synergy in cell line sensitivity screens
Prerequisites: You need working knowledge of R and a basic familiarity with Bioconductor. Experience with the data.table R package is helpful, but not required.
Workshop 4 (WS4) (May 11, 14:00-18:00; May 12, 09:00-13:00)
Lecturers: Donnacha Fitzgerald, Hosna Baniadam, Harald Vöhringer, Petr Smirnov
The aim of this workshop is to introduce single-cell (including multi-omic and spatial) methods, what can be achieved with them and principles for their analysis. It will include the following topics:
- Overview of single-cell methods
- Single-cell transcriptomics analysis
- Single-cell data integration (horizontal and vertical)
- Spatial analysis + probabilistic factor models for the analysis of single cell data
Each topic includes a 30 minutes talk followed by a 45 minutes practical component.
We will also add a consultation hour (60 minutes) at the end of the program for people to ask questions related to their own projects or to bring data for help with their analysis.
Registration is free but mandatory. Please register here (https://docs.google.com/forms/d/e/1FAIpQLSf_y78l3tCNyxm7cdWOTFWmyH4fSiHktzj-YUH7NkdPBjmVXQ/viewform?usp=sf_link) until April 28, 2023. We have 30 seats for each workshop. We might have to close the registrations before the registration deadline.