Analysis of genome-wide expression data (Bioinformatics-II)

General info

Date 

06 Apr 2010 - 06 May 2010 

Location

Academic Medical Center, Amsterdam

Website

http://www.bioinformaticslaboratory.nl/twiki/bin/v...

Keywords

Statistics, R/BioConductor, microarray data analysis, pathway analysis

Organiser

Master School of Informatics, UvA and Bioinformatics Laboratory, AMC

Contact(s)

Moerland, Perry D. Dr. ir.

Description

During this 4 week bioinformatics programme the participants acquire fundamental skills in data analysis, microarray analysis, and programming and apply these skills to real-life bioinformatics problems. This course is part of the bioinformatics track of the GRID computing master at the UvA. Other participants are welcome to attend (parts of) this course.

Module 1 - Introduction In this first module the students are given the opportunity to acquire basic knowledge in biology, bioinformatics, statistics, analysis of microarrays, and biological pathways. Depending on his/her background the student may choose to skip certain topics of this module. Please indicate which lectures you will attend when you register for this module. The participants will get a certificate listing the topics that were attended.

Module 2 - R/Bioconductor Much of data analysis in bioinformatics is done within the R/Bioconductor statistical environment. For example, many statistical methods for the analysis of microarray and other high-throughput data are available from Bioconductor. In this module you will get acquainted with R/Bioconductor and will learn to apply a range of statistical techniques to microarray data. The main topics include microarray analysis (2-dye spotted, Agilent, Affymetrix, Illumina), linear models, unsupervised and supervised learning, and the use of meta-data. Participants will get a certificate if they successfully carry out the computer exercises. Some programming experience is a plus for this module.

Module 3 - Analysis of microarray data and pathway analysis In this module you will apply what was learnt in the Bioconductor module (module 2) to a challenging microarray experiment from a recent Nature paper. You will analyze the activation status of several human oncogenic pathways. You will validate the signatures found in tumor samples derived from various mouse cancer models. Association with disease outcome of the oncogenic pathway signatures will be validated for various publicly available human cancer datasets. PhD students and post-docs can use this module to bring along their own dataset and try to analyze it using the tools learnt in the first three weeks. Good knowledge of R and several Bioconductor packages is required (therefore it is compulsory that you attend module 2). Participants will get a certificate if they successfully write a short report on their analysis efforts.