Dear all,
We still have a few places available for the course "Epigenomic Data Analysis" which will be held in Berlin from the 28th of May to the 01st of June 2018.
Registration deadline: 26th April 2018.
https://www.physalia-courses.org/courses-workshops/course31/
Instructors:
Dr. Federico Comoglio (Cambridge Institute for Medical Research (UK))
Dr. Iros Barozzi (Imperial College London (UK))
Overview
This course will introduce researchers and technical workers to the bioinformatic analysis of large epigenomic data sets obtained using Next-Generation Sequencing (NGS) technologies, with a focus on ChIP-seq, RNA-seq and DNase-seq / ATAC-seq. The course will cover the theoretical foundations of the most widely adopted algorithms and analysis pipelines, a targeted introduction to scripting in bash and R/BioConductor, and extensive hands-on tutorials using publicly available NGS data sets. At the end of this course, the students should be able to efficiently analyze their own data and identify common pitfalls of genomics data analyses.
TARGETED AUDIENCE & ASSUMED BACKGROUND
The course is aimed at researchers moving the first steps in epigenomic data analysis and / or interested in learning more about this subject. The course will offer a balanced mixture of lectures and hands-on practical tutorials using popular tools and R/BioConductor packages. Previous knowledge of genomics data formats from Illumina sequencers and exposure to bioinformatics is beneficial but not a necessary prerequisite.
Assumed Background
The participants should have some basic background in biology and understand the central role of DNA for biodiversity studies. No programming or scripting expertise is required and some basic introduction to UNIX-based command line applications will be provided on the first day. However, some basic experience with using command line and/or R is clearly an advantage as not all the basics can be thoroughly covered in that short amount of time. All hands-on exercises will be run in UNIX-environments (Linux, Mac) on remote servers. Statistical analyses will be run in R using RStudio.
For more information about the course, please visit our website
Here is the full list of our courses and Workshops