The large amounts of data derived from next generation sequencing projects makes efficient data mining strategies necessary. In the course you will learn strategies for the analysis of mRNA-Seq data as well analysis pipelines for ChIP-Seq. These strategies include
- high efficiency mapping of raw sequence tags
- clustering of sequence tags
- data integration into up to date genome annotation
- down stream analysis of tag covered regions.
The course is based on real world examples. We will show the possibilities for extending genome annotation, splice variant detection and discovery of new transcriptional units. In addition the down stream biological mining of enriched regions from ChIP-Seq will be demonstrated. This will focus on transcription factor (TF) analysis in terms of TF overrepresentation in enriched regions and the discovery of functional motifs and patterns of TFs. New insights into biological mechanisms can be gained by overlaying data from different experiment types.
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