Target of the Course
This 5 day lecture series provides an introduction to genomic data and
The main focus will be on microarray experiments, covering statistical topics
such as normalization, quality assessment, gene identification, machine
learning and inference for graphs and networks. Applications of these methods
to proteomics and other high throughput technologies will also be covered.
Computer laboratory material will be available for self-study.
Participants should have some minimal background on biological, statistical and computational aspects of microarrays, or other high-throughput data.
Participants interested in hands-on, interactive activities should
consider signing up for the lecture and laboratory series (space is
very limited). These require a basic knowledge of the R or S language.
The Focus of the Course
The focus will be on analysing and interpreting genomic data and particularly
microarray data. Other topics such as proteomics, array CGH etc. may also be covered,
depending on participant interest. Among the statistical topics: visualization, machine
learning and exploratory analyses will be emphasized. Methods for quality assessment,
for making use of biological metadata in a structured way, and for working with graphs
and networks (such as metabolic pathways) will be demonstrated. Some discussion
of methods for combining data, primarily via meta-analysis will also be presented.
The course consists of 10 morning lectures, 4 per day (8:30 - 12:00), distributed
on 5 days (Monday to Friday). Detailed case studies, suitable for self-study will be made available daily.
We don't have computing facilities but laboratory sessions will be organized. Participants, up to 30 people, willing to attend the laboratory sessions
are asked to bring their laptops (for details see below).
The labs will be worked on in groups with expert guidance (all the lecturers from the morning sessions and teaching assistants).
Participants could decide to attend morning lectures only (up to 100 participants) or both morning lectures and laboratory sessions (up to 30 participants).
The course will be given by:
Robert Gentleman [Lectures and Labs], Head of Program in Computational Biology, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle (WA), USA (member of the Bioconductor research project and member of the R Core Team).
Wolfgang Huber [Lectures and Labs], European Bioinformatics Institute, European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Cambridge, England (UK) (member of the Bioconductor research project).
Rafael A. Irizarry [Lectures and Labs], Department of Biostatistics, Johns Hopkins University, School of Public Health, Baltimore (MD), USA (member of the Bioconductor research project).
Stefano M. Iacus [Laboratory sessions only], Department of Economics, Business and Statistics, University of Milan, Italy (IT) (member of the Bioconductor research project and member of the R Core Team).
How to register
If you want to register to this course, please go to the course fees and registration page.