Genomic Data Visualization and Interpretation

Tutorial series for visualizing and interpreting omic data

Genomic Data Visualization and Interpretation

The age of cheap massively parallel sequencing has exponentially increased the availability of genome, transcriptome, epigenome, and other kinds of ‘omic profiling. Extracting biologically meaningful results and communicating this information remains challenging. This site aims to expose users to a number of “best-in-class” tools and methods for overcoming this.

We aim to provide an in-depth tutorial in the interpretation and visualization of omic data. Among the topics we will cover are: “Genome Browsing and Interpretation”, “Differential Expression and Pathway Analysis”, “Best in Class tools for visualization”, and others. Students should have a background in biology and a basic knowledge of the R programming language and linux.

This resource is structured in a modular format. Users would benefit from familiarity with topics covered in previous modules however it is not a strict requirement unless otherwise stated. Please navigate to Course to begin.

These materials have been developed with the support of Physalia-courses. The first in-person workshop was held at Freie Universität Berlin, Germany, 11-15 Sept 2017. The second iteration of this course, with improved and updated content will be held at the same location in Berlin, Germany, 8-12 April 2019 (see course page to register!). For future offerings by Physalia (including this workshop) please visit the upcoming workshops page.

Physalia-courses provides scientific training courses and Workshops in Bioinformatics, Genomics and related fields, promoting the transfer of new methods and emerging techniques to a broad range of researchers. Their goal is to build a knowledge-sharing platform between highly qualified instructors and participants at various stage of their scientific and academic career (e.g. PhD students, post-doctoral researchers, PIs). Through the courses and workshops, participants learn how to plan their projects and how to analyze their data.