Graduate School of health and Medical Sciences

Introduction to bulk RNAseq analysis
Provider: Faculty of Health and Medical Sciences

Activity no.: 3937-23-00-01
	Enrollment deadline: 05/06/2023

Date and time	19.06.2023, at: 08:30 - 21.06.2023, at: 17:00
Regular seats	30
Course fee	3,000.00 kr.
Lecturers	Anders Krogh
ECTS credits	2.50

Contact person	Eleonora Nigro E-mail address: eleonora.nigro@sund.ku.dk

Enrolment Handling/Course Organiser	PhD administration E-mail address: phdkursus@sund.ku.dk

Aim and content This is a generic course. This means that the course is reserved for PhD students at the Graduate School of Health and Medical Sciences at UCPH. Anyone can apply for the course, but if you are not a PhD student at the Graduate School, you will be placed on the waiting list until enrollment deadline. After the enrollment deadline, available seats will be allocated to the waiting list. The course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD students at NorDoc member universities. All other participants must pay the course fee. Learning objectives A student who has met the objectives of the course will be able to: 1. Gain insight into how to design an RNA-seq experiment 2. Preprocess sequencing reads 3. Analyze bulk RNAseq data using the R package DESeq2 4. Know best practices for performing Differential Expression Analysis 5. Annotate and interpret their results Content This course is an introduction for how to approach bulk RNAseq data, starting from the sequencing reads. It will provide an overview of the fundamentals of RNAseq analysis, including read preprocessing, data normalization, data exploration with PCAs and heatmaps, performing differential expression analysis and annotation of the differentially expressed genes. Participants will also learn how to evaluate confounding and batch effects in the data. The course will further touch upon laboratory protocols, library preparation, and experimental design of RNA sequencing experiments, especially about how they influence downstream bioinformatic analysis. Participants The course is intended for PhD students at SUND who are interested in learning how to treat their bulk RNAseq data. The course is specifically targeted towards medical and biological researchers who are looking to strengthen their bioinformatics analysis skills, though PhD students from all disciplines are welcome. Requirements - Working knowledge of the command line, R language, RStudio and Rmarkdown is mandatory. - Basic knowledge of RNA sequencing technology. - Basic knowledge of data science concepts such as principal component analysis, clustering and statistical testing. Relevance to graduate programmes The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH: All graduate programmes Language English Form This course is a 3-day course composed of a combination of lectures and exercise sessions. Course director Anders Krogh,? Professor, Head of Center for Health Data Science,? Center for Health Data Science,? anders.krogh@sund.ku.dk Teachers Jose Alejandro Romero Herrera PhD, Data Scientist, Center for Health Data Science, jose.romero@sund.ku.dk? Henrike Zschach PhD, Data Scientist, Center for Health Data Science,? henrike.zschach@sund.ku.dk Adrija Kalvisa PhD, Special consultant reNEW adrija.kalvisa@sund.ku.dk Diana Andrejeva, PhD, Data Scientist, Center for Health Data Science,? andrejeva@sund.ku.dk? Dates 19 - 21 June 2023, from 08:30 to 17:00 Course location Holst auditorium, Maersk Tower, Faculty of Health and Medical Sciences, Panum,? Blegdamsvej 3B, 2200 København. Registration Please register before 05 June 2023 Expected frequency This course is run twice a year. Next course will be held approximately January 2024. Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules. Applications from other participants will be considered after the last day of enrolment. Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.

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