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Statistics for Life Sciences in R Course

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Institute of Molecular Genetics of the Czech Academy of Sciences, Vídeňská 1083, Praha 4 Map

About

The goal of this hands-on workshop is to equip participants with the essential tools to independently analyze and interpret biological data using R and UNIX frameworks. You will learn how to extract key insights from your data and summarize the results with graphical representations. You can choose to participate in the entire 5-day course or select individual modules based on your experience and goals. This course is ideal for beginners and those looking to enhance their R skills for statistical applications. It also serves as a prequel to a planned course on single-cell RNA-seq analysis set for autumn 2025.
 
The first module provides a practical introduction to data analysis in R, combining data visualization techniques with the basics of the UNIX command line. Participants will begin with lectures on RStudio and data visualization before exploring foundational concepts in UNIX. Additionally, functional enrichment analysis using g:Profiler will be presented.
 
The second module focuses on key statistical methods in R, equipping attendees with essential tools for biological data analysis. Topics covered will include hypothesis testing for numerical and categorical data, linear models, correlation and regression.
 
Dates: 23.-29.04.2025
 
Location: Institute of Molecular Genetics of the Czech Academy of Sciences, Vídeňská 1083 Praha 4, Jágr’s hall
 
Maximum capacity: 25 participants
 

Programme

Module 1 Wednesday 23rd-Friday 25th 

     Day 1 – Wednesday – RStudio basics

        9:30 – 11:00  Understanding basic R data structures
     11:00 – 11:15  Break
     11:15 – 12:15  Understanding basic R data structures continues
     12:15 – 13:15  Lunch
     13:15 – 14:45  Data transformation with tidyverse
     14:45 – 15:00  Break
     15:00 – 16:00  Data transformation with tidyverse continues

     Day 2 – Thursday – Data visualisation theory & Data visualisation with RStudio

        9:00 – 10:30  Data visualisation theory: How to choose appropriate chart types
     10:30 – 10:45  Break
     10:45 – 12:15  Data visualisation theory: Common mistakes and best practices
     12:15 – 13:15  Lunch
     13:15 – 14:45  Data visualisation with RStudio: Grammar of graphics
     14:45 – 15:00  Break
     15:00 – 16:30  Data visualisation with RStudio: Overview of geoms
     16:30 – 16:45  Break
     16:45 – 17:45  Data visualisation with RStudio: Customization and patchwork

     Day 3 – Friday – Shell novice & Introduction to g:Profiler

        9:00 – 10:30  The Unix shell: Introduction and navigating files and directories
     10:30 – 10:45  Break
     10:45 – 12:15  The Unix shell: Working with files and directories
     12:15 – 13:15  Lunch
     13:15 – 14:15  The Unix shell: Pipes and filters and finding things
     14:15 – 14:30  Break
     14:30 – 16:00  g:Profiler: Functional enrichment analysis in g:Profiler
     16:00 – 16:15  Break
     16:15 – 17:45  g:Profiler: Conversion tools in g:Profiler and programmatic access

Module 2 Monday 28th-Tuesday 29th 

     Day 1 – Monday – Introduction to statistics with R

        9:30 – 11:00  Warm-up with Exploratory data analysis (practical),
                                      Hypothesis testing (theory)
     11:00 – 11:15  Break
     11:15 – 12:15  Hypothesis testing (practical)
     12:15 – 13:15  Lunch
     13:15 – 14:45  Multiple testing correction (practical),
                                      Non-parametric test for two samples (theory)
     14:45 – 15:00  Break
     15:00 – 16:00  Non-parametric test for two samples (practical)

     Day 2 – Tuesday – Introduction to statistics with R

        9:30 – 11:00  Multiple sample testing (theory + practical),
                                      ANOVA, Tukey Post-hoc test, Kruskal-Wallis     
     11:00 – 11:15  Break
     11:15 – 12:15  Correlation and regression (theory + practical)
     12:15 – 13:15  Lunch
     13:15 – 14:45  Linear mixed models (theory), categorical data (theory),
                                       χ2 test (practical)
     14:45 – 15:00  Break
     15:00 – 16:00  Fisher’s exact test (theory, practical)

Instructors

The course is taught by bioinformaticians Diana Pilvar, Priit Adler and Marilin Moor from University of Tartu who are part of the Estonian Elixir node.

 

Requirements

Module 1 – no previous experience with R programming or UNIX is required.
 
Module 2 – test your knowledge at https://www.evamariakiss.de/tutorial/rquiz/quiz_fundamentals.php
Please note, if you get >= 50%, you are eligible for this course. Else, try to find a Basics in R course before attending this one – or attend module 1!”
 
Participants are encouraged to bring their own laptops with specific software installed, however workstations will be provided upon request. Software requirements will be sent to all participants upon registration. For any help with software installation please reach out to jiri.netusil@img.cas.cz, rajendra-kumar.labala@img.cas.cz  or michal.kolar@img.cas.cz
 

Registration

Registrations for both modules are closed. 
 

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