Statistical analysis of ~omics data

General info

Date 

13 Dec 2010 - 17 Dec 2010 

Location

Wageningen, the Netherlands

Website

http://www.graduateschool-eps.info/index.php?optio...

Organiser

Graduate Schools VLAG and EPS and Wageningen UR Plant Breeding

Contact(s)

Dr. Chris Maliepaard

Level

PhD

Targetgroup

Systems Biology

Life Science

Bioinformatics

Description

>>NBIC is sponsoring a number of seats in this course, please contact Celia van Gelder for more information.

Background

Nowadays increasing numbers of complete genomic sequences are available and high-throughput methods have been developed to study gene expression (transcriptomics), proteins (proteomics) and metabolite levels (metabolomics). Because high-throughput methods generate large datasets, special analysis and visualization techniques are required to extract relevant information to help elucidating the functions of genes, proteins and metabolites, the interactions between these molecules and the underlying regulatory mechanisms. Statistical analysis of these data is non-trivial since in many cases the number of genes/metabolites outweighs the number of samples by hundreds or thousands.

Course design

In order to successfully interpret experimental results generated by high-throughput ~omics methods we will teach the principles underlying preprocessing, statistical analysis and visualization of large datasets derived from transcriptomics and metabolomics experiments. The emphasis will be on statistical aspects and analysis. Relevant software will be mentioned and some will be used during hands-on exercises. During the course students are provided with a syllabus, handouts, exercises and an overview of relevant literature and Internet links.