Admission requirements
Before enrolling in this course, students should have a basic understanding of the R programming language.
Description
The biomedical data analysis life-cycle begins with data collection from various sources, followed by pre-processing steps such as cleaning and organising the data for analysis. Then, statistical techniques are employed to derive insights, identify patterns, or make predictions. Next, interpretation of the results is performed to ensure their reliability and relevance. Finally, findings are communicated through publications, reports etc. All steps may be re-iterated in this process.
This is a one week practical course on biomedical data analysis life-cycle where you will carry out steps in the life-cycle on a real life data.
The main themes:
Understand the data: identify data types, check value ranges and units, relate to experiment
Data preparation: join data from separate tables, group and summarize rows, clean (remove/correct invalid values), etc.
Exploratory analysis: visualisation of raw and preprocessed data
Modelling: fitting simple statistical models, extraction of model parameters
Communicating the results
Course objectives
The student implements R code which allows (in a reproducible way) to:
Prepare biomedical data for analysis;
Combine relevant data from various sources;
Carry out data quality control;
Apply exploratory data analysis using visualisation and tabulation techniques;
Communicate the results.
Timetable
All course and group schedules are published on MyTimeTable.
The exam dates have been determined by the Education Board and are published in MyTimeTable.
It will be announced in MyTimeTable and/or Brightspace when and how the post-exam feedback will be organized.
Mode of instruction
Seminar.
Assessment method
Written examination with short questions.
Reading list
For the complete reading list for the bachelor of Biomedical Sciences, see the Study Materials List BW 2025-2026.
Registration
To participate in workgroups and exams students must register with uSis.
Contact
Szymon M. Kiełbasa, (smkielbasa@lumc.nl)
Ramin Monajemi, (r.monajemi@lumc.nl)
Marian Beekman (M.Beekman@lumc.nl)
Niels M.A. van den Berg (N.M.A.van_den_Berg@lumc.nl)
Remarks
The course assumes that students are familiar with R language and with R package.