Course information: https://www.scilifelab.se/events/rna-seq-data-analysis/ Course leader: Johan Reimegård ([email protected]) Local Course leaders: Jeanette Tångrot ([email protected]) and Nina Norgren ([email protected]) #training Course content: This course will cover both theoretical and hands-on exposure to current topics in RNA-seq analysis. Lectures from experts in RNA-seq and biostatistics will cover a range of cutting-edge issues in RNA quality control, transcript assembly in model and non-model organisms, differential expression analysis and downstream analysis using other types of data. A selection of tutorials will familiarize you with concepts of mapping, quality control of your RNA-seq data, de novo assembly, assembly using a reference, differential expression analysis and downstream enrichment analysis. Topics covered will include: RNA seq introduction RNA seq transcript assembly and annotation RNA seq read mapping programs RNA seq QC analysis Differential expression analysis Gene set enrichment analysis Entry requirements: Basic knowledge in linux is a requirement! We will not teach Linux at the course and you will have considerable trouble to follow the practical sessions if you are not reasonably used to work in a linux environment. Be able to bring your own laptop for the practical computational exercises. Experience working in R and some programming/scripting experience is desirable, but not required. Experience working on the SNIC center Uppmax is desirable, but not required. Experience working with NGS data analysis is desirable. Participants of the SciLifeLab Course “Introduction to Bioinformatics using NGS data” (or alike) are most welcome to apply, but this course is not required. Some overlap with this course is expected, but the workshops will be considerably more detailed on the covered topics. There are a maximum number of allowed participants. If we receive more applications, participants will be selected based on several criteria. Selection criteria include correct entry requirements, motivation to attend the course as well as gender and geographical balance.