BMB830: Biostatistics in R I (5 ECTS)

STADS: 01014301

Master's level course

Teaching period
The course is offered in the autumn semester.

Teacher responsible
Veit Schwämmle, Lektor, Ph.d.
Tlf.: 6550 9999 Email:

Group Type Day Time Classroom Weeks Comment
Common I Monday 12-14 U143 36
Common I Monday 12-14 U61 37
Common I Monday 14-16 U142 39
Common I Monday 14-16 U10 41
Common I Tuesday 10-12 U56 38
Common I Tuesday 10-12 U24 40
Common I Wednesday 12-14 U61 36,39
Common I Wednesday 10-12 U61 37
Common I Wednesday 12-14 U17 38
H1 TE Monday 12-14 U61 43
H1 TE Wednesday 12-14 U61 37
H1 TE Wednesday 12-14 U17 41
H1 TE Wednesday 12-14 U21 43
H1 TE Friday 14-16 U61 37
H1 TE Friday 10-12 U21 38-39
H1 TE Friday 10-12 U61 40
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Academic preconditions:
Students taking the course are expected to:

Course introduction
Modern experimental platforms generate large sets of often noisy data that requires its processing by appropriate analytic and statistical methods. High-confidence data interpretation is built upon correct application of methods such as statistical models and pattern recognition. Furthermore, proper visualization of the results helps presenting and understanding the results. This course introduces the students to the main concepts of biostatistics, data analysis and visualization, so they understand the principles to design and apply work flows that handle a certain data type. The course will have a theoretical and a practical part, with the objective to provide general understanding of data analysis and application of bioinformatics tools.

Among currently available software suits, the R scripting language became very popular to deal with biostatistics and analysis of large data sets, as it (i) provides a vast number of statistical tools, (ii) allows adaptation of the analysis to any experimental design, (iii) offers simple commands to operate on entire data sets, (iv) provides a wide range of methods for data visualization and (v) has a large and active community of researchers developing new tools. However, it requires the user to acquire scripting skills to take advantage of the many features.
The course will introduce the students to basic programming of R scripts, data visualization and basic statistical models necessary to deal with data from modern high-throughput experiments.

Expected learning outcome
The learning objectives of the course are that the student demonstrates the ability to: Subject overview
The following main topics are contained in the course: Literature
There isn't any litterature for the course at the moment.

This course uses e-learn (blackboard).

Prerequisites for participating in the exam
Tutorial and exercises. Pass/fail, internal marking by teacher (01014312)

Assessment and marking:
Oral examination. External marking, Danish 7-mark scale (01014302)

Allowed aids: Blackboard / Whiteboard.

Expected working hours
The teaching method is based on three phase model.
Intro phase: 20 hours
Skills training phase: 16 hours, hereof:
 - Tutorials: 16 hours

Educational activities

Educational form

This course is taught in English.

Course enrollment
See deadline of enrolment.

Tuition fees for single courses
See fees for single courses.