PhD Courses in Denmark

After you have taken this course, you will be able to do state-of-the-art bioinformatics analysis of single-cell data. The main focus in the course is on single-cell RNA-sequencing but we will also cover other single cell technologies.

A student who has met the objectives of the course will be able to:

• independently seek out and obtain relevant information about single-cell data analysis.
• list various single-cell technologies along with relevant biological use-cases.
• assess strengths and weaknesses with various experimental setups.
• list various bioinformatic analysis tools and what they are used for.
• discuss strengths, weaknesses, and key parameters for various analysis approaches.
• apply and interpret state-of-the-art bioinformatic analysis to single-cell data in the biological context of the data.
• use R to organize, modify, and visualize data.
• as a group design and execute a single-cell analysis project.
• clearly present obtained results orally using proper visual aids.
• Explain the principle behind how GenAI (such as ChatGPT) works and how that can lead to hallucination.
• Explain the difference in learning outcomes when using GenAI (such as ChatGPT) as a tutor vs using GenAI as an answer machine.
• Use GenAI (such as ChatGPT) as a sparring partner in an applied project to augment your work.

The first part of the course will introduce and have you work with various single-cell technologies and analyses, including, but not limited to: • Single-cell RNA-seq • Dimensionality reduction, integration, clustering, and cell-type annotation • Downstream analysis such as differential expression and differential cell type abundance • Other single cell technologies In the second half of the course, you will have to do a group-based project on real data. For this project, you can work on data we provide or bring your own data (e.g., from your master thesis or PhD project) as long as the dataset has been approved by a teacher.