Multivariate analysis for exploration and visualization of biological data

Date 20 April 2016
Speaker(s) Delphine Grun
ECTS 0.25
Fees *academic: 50 CHF   -   for-profit: 0 CHF
Cancellation deadline 12 Apr 2016
City Lausanne
*academic fee includes non for-profit organisations as well as unemployed participants at the time of application.


Multivariate data sets are prevalent in many biological research fields, and they are often approached from an exploratory perspective, with the aim of generating new and potentially relevant hypotheses and reveal previously unknown structure and patterns. An initial exploratory analysis can also be helpful for detecting anomalies in the measured data. Having a graphical representation of the data is very useful for such exploratory analysis. However, since the human brain is essentially limited to interpreting at most three-dimensional graphical representations, efficient summarization methods must be applied before a high-dimensional data set can be visually explored.

In this workshop, we will discuss some of the most common methods for summarizing and creating graphical representations of multivariate data, such as principal component analysis (PCA), multidimensional scaling (MDS) and correspondence analysis (CA).


This course is intended for life scientists who have attended the course "An Introduction to R" or a similar course and have a basic knowledge in mathematics (matrix operations, …).

Learning objectives

At the end of the course participants should be able to:

  • understand the usefulness of multivariate analysis and recognize case when useful to use it.
  • understand the different type of data between coordinate matrix, frequency table, dissimilarity matrix and recognize them.
  • understand the basic idea of ordination and linear combinations.
  • understand the three methods presented (PCA, CA, MDS) and implement them in R.


Knowledge / competencies:

Participants should have a basic knowledge in mathematics (matrix operations, …).


Participants should install the R open source software on their laptop and should have a basic knowledge of it.


The registration fees for academics are 50 CHF. This includes course content material and coffee breaks. Participants from non-academic institutions should contact us before application.

Deadline for registration and free-of-charge cancellation is set to April 12. Cancellation after this date will not be reimbursed. Please note that participation to SIB courses is subject to this and other general conditions, available here.

You will be informed by email of your registration confirmation.


University of Lausanne, Génopode Building, room 2020

Additional information

The course will be taught by Delphine Grun from the Bioinformatics Core Facility at SIB.

Coordination: Diana Marek, Training group at SIB

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