Five days hands-on computer course for biological and clinical researchers whose research involves experiments that generate gene expression data. The course focuses on microarray and next-generation sequencing gene expression data, but some concepts may be applicable to other types of genomics data. Most of the speakers (and therefore examples) have a biomedical background. Software packages used are freeware, including the statistical software R, Bioconductor, Cytoscape and web tools. The total number of participants is limited to 40.
Date: June 22-26, 2015
- The participant has insight in the issues involved in good experimental design, including power to detect differential expression in microarray and next-generation sequencing data.
- The participant knows and can perform analysis steps in expression data analysis, visually present and judge the results for:
– quality control and preprocessing,
– finding differentially expressed genes,
– cluster analysis,
– classification analysis,
– pathway testing.
- The participant has insight in the different algorithms and options available to perform an analysis, and can make an informed choice.
- The participant knows the pitfalls of existing analyses and is able to critically judge the statistical analysis of expression data performed by others.
The course is intensive, and covers the basic concepts and methods required for expression data analysis. Presentations are followed by hands-on computer sessions to directly apply and get more insight in the analysis methods. One afternoon is dedicated to the analysis of a new data set, allowing the students to refresh and extend their analysis skill. After the course, the presentations, practicals and test data will remain available for future reference. Software packages used are freeware, including the statistical software R, Bioconductor, Cytoscape and web tools.