Pre-course assignments and all course material will be available in the link below soon!
Lectures give insight on how biological knowledge can be generated from RNA seq experiments and illustrate different ways of analysing such data. Practicals consist of computer exercises where participants apply statistical methods to analysis of RNA-seq data under the guidance of lecturers and assistants. Familiarity with the technology and biological use cases of high throughput sequencing is required, as is some experience with R/Bioconductor. Own RNA-seq data can be analysed on the course.
Computational course consisting of pre-course reading material and introductory computer practicals; an intensive course of 5 days; and an on-line exam.
Takes place in a regular classroom that has two times as many seats as there are participants on the course. Requires an own laptop computer (any OS is fine).
Using a tailor-made virtual machine that can be installed on a personal laptop or used on the CSC cloud through a web-browser.
On-line exam consisting of: questions based on the pre-course reading material and course lectures; and data analysis tasks utilising the learned methods.
Main teacher: Nicolas DelHomme, Umeå University, Sweden.
1-2 weeks before the course. Reading of selected publications. On-line practical that familiarises with the computational methods used (access to the course computer and basic Linux command line work). Possibility to install the program package locally or use the cloud computer.
5 day intensive course consisting of lectures and practicals. Active learning feedback with Socrative.
Exam within 7 days from the end of the main course.