Advanced transcriptomics analysis
Lausanne, 17-21 June 2013
This five-day course on advanced methods for transcriptomics analysis picks up from where the Introduction to microarray analysis/Analysis of differential gene expression courses left, and explores how transcriptomics data can be further integrated and interpreted to yield biologically relevant information. It will be assumed that participants have knowledge corresponding to the Introduction to microarray analysis/Analysis of differential gene expression course, in particular concerning normalization of microarray and RNAseq data and how to find differentially expressed genes between different conditions in a single dataset.
The course will consist of theory and practical exercises. Participants should bring their own computers with the R statistical software installed. In line with the prerequisites indicated above, participants should ideally already know how to conduct a simple microarray or RNAseq data analysis with R and Bioconductor.
This course is organized by the Bioinformatics Core Facility and will be held in Lausanne.
We plan to cover the following topics:
- How and where to find external data, and how to integrate transcriptomics data from different platforms. Use of data repositories such as GEO and TCGA, gene mapping and cross-platform matching, gene identifiers, etc. Meta-analysis.
- Prediction, classification and clustering of high-dimensional data. Finding gene signatures and validating them in independent data sets.
- Data structures for transcriptomics analysis with R.
- Annotation resources.
- Gene set/pathway analysis.
- Integration of transcriptomics data with other types of genomic data.
Registration is closed
The registration fee for Swiss academics is 200 CHF. (Some doctoral programs may subsidize the course; please contact your doctoral program for more information).
Participants from the industry or from abroad should contact us.
The fees include course content material, coffee breaks and a social dinner.
ECTS accreditation: 2 credits
Important: successful participating graduate students will have to inquire if these credits are accepted by their respective graduate schools.
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