Multivariate analysis for exploration and visualization of biological data
12 April 2016
For-profit: 0 CHF
No future instance of this course is planned yet
Overview
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).
Audience
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.
Prerequisites
Knowledge / competencies:
Participants should have a basic knowledge in mathematics (matrix operations, …).
Technical:
Participants should install the R open source software on their laptop and should have a basic knowledge of it.
Application
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.
Location
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
You are welcome to register to the SIB courses mailing-list to be informed of all future courses and workshops, as well as all important deadlines using the form here.
For more information, please contact training@sib.swiss.