Week 2 of F1L Internship Emulator: The Paper

Read the Paper

One of the greatest shortcomings in modern life science education is not forcing students to read more primary literature. So one of the first things I will ask you to do, even before you touch any data, is to read a paper.

Read Kinker et al. (DOI: 10.1038/s41588-020-00726-6). You can find it directly online or from the F1L GitHub repo.

To start, try to read through the entire paper in 1 hour. Don’t get stuck on methodological details (yet) until you have an overview of the entire study. What did the authors do? Why did they do it? What did they learn?

After your first read-through, take time to revisit any parts still unclear to you, including some of the methods. Prioritize your understanding of the parts of the paper related to Figures 1-4.

Don’t be surprised if you end up spending 4-8 hours just to digest this paper. And it’s ok if you don’t understand 100% of the paper; even 50-75% comprehension is already a good starting point. As you explore the data from this paper in future weeks, your understanding of the paper should deepen.

Test Your Own Understanding

Here are a few questions to help you gauge your understanding of the paper. Add your responses to these questions as notes to the memo you started in Week 1. Once you have done so, share a link to your GitHub repo in our Discord.

• How did the authors handle the potential caveat of co-culturing cell lines before profiling by scRNA-seq? Why do you think that caveat was or was not adequately addressed?

• The authors identified discrete subpopulations of cells within a subset of individual cell lines (Fig. 2A-B). What might be the reason why some cell lines have these discrete subpopulations while others do not?

• What are Recurrent Heterogeneous Programs (RHPs) and how were they defined?

• How do the identified RHPs relate to in vivo programs of heterogeneity in tumors, and what evidence supports this relationship?

• Where can you download the scRNA-seq data as shown in Figure 1B?

This list of questions is not exhaustive. You should come up with other questions to test your own understanding. You might also find yourself reading some of the papers in the References section of Kinker et al.

Download the Data

Download the scRNA-seq data as shown in Figure 1B and place it in an organized directory structure where you will also keep your code and intermediate outputs. This is to get everything ready for the following week.

Resources

• Introducing Figure One Lab (F1L)

• Introducing the F1L Internship Emulator

• Week 1 of F1L Internship Emulator: The KSQ

• Discord for participants

• Suggestions for how to analyze scRNA-seq data from Fabian Theis’s lab, one of the leaders in this kind of analysis. No need to read this completely, as it is quite long, but get familiar with the table of contents.

• A demo by Mark Sanborn showing how he analyzes scRNA-seq data: Part 1 and Part 2