Organizer: German Cancer Research Center - DKFZ
Registration necessary: yes
Module 3 - practical course on data analysis, September 27 - 29, 2017, conducted via the HD-HuB of the de.NBI program
The SEEDED - Sequencing Analysis of Epigenetic Deregulation in Disease - summer school is targeted at PhD students and postdocs working in systems medicine projects like those conducted in the German e:Med program that involve deep sequencing (epi)genome and transcriptome analysis.
Application Deadline was May 28, 2017 via online form
SEEDED will train the participants on how to conduct the complete work-flow for the integrative analysis of epigenetic deregulation in primary disease cells. Complementary multi-readout data sets that map the DNA methylome, active enhancers or promoters as well as the transcriptome will be applied. In this manner SEEDED will advance the participants' skills for interdisciplinary work that combines experimental data acquisition and theoretical analysis. A specific focus will be on exploiting the multiple deep sequencing readouts for integrative systems medicine and personalized medicine approaches.
Candidates should provide an abstract on their current research as well as a letter of motivation for their application. The letter should described how the applicant's research would profit from attending the SEEDED course. A total of 14 participants will be selected that attend all three SEEDED modules described below. Selecting only one or two modules is not possible. There is no registration fee. For the selected participants all costs associated with course participation and accommodation will be covered by the program. Only travel to and from Heidelberg has to be organized and paid by the participants themselves.
Module 3, analyzing and interpreting RNA-seq, WGBS and ATAC-seq data will be a practical course with introductory seminars on the computational methods used. It will teach a hands-on workflow for the analysis of the sequencing data generated by the course participants in Module 2. It will be based on a rich multi-readout data set that allows it to address how DNA methylation, enhancer activity and transcription are correlated. A short introduction to basic computer skills (R, command line, etc.) needed in the course will be taught during the first day. Various analysis approaches applied in the context of reaching the learning goals in use workflows in R and Bioconductor. Sequence read mapping will also be covered in this part. On day 2 and 3, tools used for interpretation and visualization will be introduced, these include software for the identification and integrative analysis of differential gene expression, gene fusions and splicing variants as well as of epigenetic regulation of gene expression by differential methylation of CpG islands. Furthermore, the analysis of the active enhancer landscape from ATAC-seq data will be covered. The bioinformatical analysis taught in the course will serve as the foundation and starting point for developing integrative systems models that describe the function of epigenetic networks and effects that occur in response to treatment with epigenetic drugs that target chromatin modifiers.
The course will be part of the German Network for Bioinformatics Infrastructure (de.NBI) and conducted via the Heidelberg Center for Human Bioinformatics (HD-HuB) and its partner project on epigenetic analysis (de.NBI-epi).