We will be delivering a workshop on advanced R and bioinformatics applications for visualization and interpretation of genomic data. While the course has advanced modules, we try to start from basic principles and build from there. Many of the genomic data interpretation and visualization principles covered are meant to be cross applicable to data from almost any species or experimental system.
Date and location: Berlin, 8-12 April 2019
To get a sense of the kinds of content covered you can browse the course site: https://genviz.org/
Attendees will learn to visualize and interpret results from real genome/exome/RNA-seq data sets generated at the McDonnell Genome Institute at Washington University School of Medicine. These data will be analyzed to determine previously known as well as potentially novel interpretations. Since the example data are not simulated or arbitrarily filtered, interpretation and visualization will be performed in the context of representative levels of sequence error, and other sources of technical and biological noise.
The majority of class time will be spent on hands on exercises with only strategic lecturing on core principles and sources of confusion in genomic data interpretation. Students are highly encouraged to bring their own data to discuss with the instructors and to immediately apply skills learned.
Who should attend: This workshop is aimed at researchers and technical workers who are analyzing some kind of omic data (e.g. WGS, exome, RNA-seq, variant files, etc.). Examples demonstrated in this course will primarily involve primarily genome/transcriptome data but many of the concepts learned will be applicable to model organisms, metagenomics, simulated data, etc.
Many find performing data visualization in R in general, and using ggplot in particular to be very unintuitive. We hope that by the end of this course students will be comfortable performing powerful genomic data manipulations in R and exploring these data by visualization using ggplot.
This course is delivered in collaboration with Carlo Pecoraro and Physalia. For full course registration details, please visit: https://www.physalia-courses.org/courses-workshops/course14/
