:section_navigation => has_subnav?(@item) && subnav_items(@item).length > 0)
%>
- Home
- Help
- Courses and Conferences
- 2010
- Computational Statistics for Genome Biology 2010
Computational Statistics for Genome Biology 2010
Bressanone-Brixen, Italy
2010-06-13 ~ 2010-06-18
Instructors
- Patrick Aboyoun
- Simon Anders
- Robert Gentleman
- Florian Hahne
- Wolfgang Huber
- Audrey Kauffman
- Martin Morgan
- Grégoire Pau
Description
This one week intensive course is intended to give insights into recent advances in statistical and computational aspects of the design and interpretation of microarray experiments. The topics will include all aspects of the data analysis of microarray experiments for transcript profiling and ChIP-chip. The course is intended mainly for researchers with a basic understanding of microarray technology and its statistical and computational challenges. The four practical sessions of the course will be most beneficial for participants that are able to converse in a programming language such as R.
Materials
- L03: Overview of Bioconductor packages for short read analysis
- L05: Microarray normalisation
- L06: Array quality metrics
- L08: Multiple testing and independent filtering
- L09: Processing data from high-throughput sequencing experiments
- L10: Rsamtools and Work Flows with Larger Data
- L12: Bioconductor sequence infrastructure
- L13: Gene and genome annotation
- L14: Processing data from high-throughput sequencing experiments II
- L16: Cell-Assay Image Analysis
- L17: ChIP-Seq Concepts and Applications
- L18: Differential expression analysis for sequencing count data
- L19: Clustering and classification with microarray data and images
- Basic R tutorial
- Lab 3: Reading and Manipulating Short Reads
- Lab 4: An Introduction to Rsamtools
- Lab 7: A ChIP-Seq Workflow
- Lab 8: RNA-seq Use Case
- CSAMA10_0.0.3.tar.gz package - An R package
containing slides and exercise material. Download, then install in R using
install.packages("CSAMA10_0.0.3.tar.gz", repos=NULL, type="source")