https://padlet.com/gokhanakman2/j3ut3z0lu8g0c111 The following case study describes the teaching activity organized by UCL's Department of Interventional Science for postgraduate students. The session aims to introduce students to Spatial Transcriptomics data analysis methods. This session's learning outcomes are: • The students should be capable of using the spatial data analysis software independently. • The students should have the ability to design a pipeline for data analysis. • The students should be able to download public data sets, generate and test their hypotheses using these data sets. The cohort consists of 12 postgraduate students. The students are from various backgrounds, mainly from the biological and medical sciences. One has a BSc in mathematics. Nobody in the group has computer analysis skills for genetics. One student has experience for R programming. The classes were constructed in a hybrid format (online + face-to-face), with one half of the students in the classroom and the other half participating online. A variety of preparation materials were provided to the students before the lesson, including videos, presentations, and links for downloading the software and public datasets. At the beginning of the lesson, I opened a discussion and I asked question about videos and preparation materials to measure students’ knowledge levels. I observed that most of the students did not use the preparation materials. They mentioned that they were confused about how to download software and public data sets from the links. We began with the presentation. I gave information about general spatial transcriptomics techniques and an historical perspective of the scientific studies in the field. I felt the students’ motivation was low in this stage. When I began to talk about Visium Technology, which is what we are currently using in the laboratory, all the e students became engaged. They began to ask questions and to take notes. After the theoretical section was completed, I asked to students discuss what public dataset they would like to use. I gave an opportunity for students to express their ideas as a snowball activity. They wrote down their ideas on the white board. They mainly agreed on working with prostate cancer data sets, which is relevant to our current studies in the department. Firstly, we downloaded public datasets. When we tried to download the required software for analysis, most of the students were confused about which version of the software needed to be downloaded. The main problem was related to their computers’ operating system or configuration. I helped students at this stage. This step unexpectedly took more time than I anticipated. When we ran the software, all the students expressed their excitement about the study. They were motivated and fully engaged. I grouped the students. I asked them to visualize the expression level of their favourite gene sets. I gave them 20 minutes for visualization of their analysis results. Then I asked them to generate a hypothesis related with their gene sets and prostate cancer. During the preparation I helped each group about their technical problems. One of the members from every group presented their results and interpretations as a graphics and plots. Other students were asked questions and they were replied. We talked about other third-party analysis software about further analysis. [I don’t understand what you mean]. I listed related software and I shared related resources. We open a discussion about which software they needed for further data analysis. We talked about licence requirements and discussed alternative open sources options. I summarised for the students the computational analysis methods in spatial transcriptomics studies. We discuss these ideas in an open discussion. I reviewed the lesson objectives. We discussed next steps and learning resources in this area. After the lesson I set up a Moodle forum and students shared their analysis report, and I gave feedback for their analysis. en-us 2022-03-22 17:51:41 UTC 2022-03-22 17:56:14 UTC hello@padlet.com gokhanakman2 https://padlet.com/gokhanakman2/j3ut3z0lu8g0c111/wish/2108109200 2022-03-22 17:56:14 UTC https://padlet.com/gokhanakman2/j3ut3z0lu8g0c111/wish/2108109200