 Okay, great. Thank you so much for your patience. I apologize for whatever technical difficulty caused that, but here we go. So yeah, I'll be talking today about leveraging R for cancer informatics training. I'm currently at the Fred Hutchinson Cancer Center, but a lot of this work was done at Johns Hopkins Bloomberg School of Public Health. Next slide. If you're interested in having the slides for this talk later, I put the link of course in the chat, but you can also find it on my website under presentations under talks. Next slide. All right, I'm gonna start out with a little bit of motivation as to why we're doing this project. Next slide. Okay, for one, I know that we're all very busy, especially cancer researchers. And, you know, after the pandemic, I don't know about you, but it just feels like it continuously gets more and more busy. Next slide. And technology is changing very quickly and it's extremely hard to keep up with everything in terms of what we can do in terms of measuring different types of data and learning how to deal with that data. Next slide. And so at the Johns Hopkins Data Science Lab, our solution often tends to go in the direction of education. And so that's where we started to think about how we could solve this problem. Next slide. And in particular, we're also focused on democratizing education material and making it as freely available as possible. And we think that that holds the power, particularly for informatics education, to improve diversity in medicine and help with health disparities. Next slide. And so the major idea is that cancer research could advance faster if informatics was more accessible. Next slide. And so we think of two major archetypes in terms of the audience that we're trying to target right now, which would basically be the researchers currently doing cancer research. So we have clinical or translational wet bench scientists who often want to do more informatics work. And we thought, how can we make it easier for them to use informatics tools that are currently available? Next slide. And then our second archetype is the busy bioinformaticist or bioinformatician who is developing tools and wants people to use them successfully, but may also want to learn themselves how to use a different data type. So how can we provide education for these people as well as opportunities to help their tools reach more people? Next slide. And so we often have a situation where we have someone who may be relatively new to informatics or new to analyzing a particular type of data. And they're excited to use it and find some software that may help them. Next slide. But unfortunately, often they encounter some error that has jargon they don't understand. And it becomes a very inefficient and confusing process. Next slide. And so they often go to a nearby collaborator to ask for help. Next slide. But often that collaborator is also getting lots of requests and lots of data sent to them, sometimes in insecure ways with thumb drives and it's causing a lot of inefficiency. Next slide. And so ultimately cancer informatics is hindered by this gap between different types of experts. And this is something that we really want to target from the side of tool usability and also helping with user preparedness. Next slide. And ultimately by decreasing this gap in expertise we think that we can really catalyze informatics to advance cancer research. Next slide. And so this project is funded by the Informatics Technology for Cancer Research ITCR program from the NCI or National Cancer Institute. Next slide. And we created something called the ITCR Training Network or ITN with the idea of catalyzing informatics research through training opportunities. And you can find out more about this network at ITCRtraining.org. Next slide. And so ultimately we're hoping to enhance usability for cancer informatics tools by helping tool developers improve practices for informatics works, particularly for trainees that are new to informatics and to enhance awareness and access for informatics resources. Next slide. And so the elements of ITN are number one to make courses about informatics but also to provide infrastructure and tools for not only ourselves to create courses but for others to really leverage the knowledge of the collective expertise. We also provide live education opportunities because we see the value of that and as well as enhancing cancer research community engagement. Next slide. And so here's our ITN team. We have four principal investigators including myself and Jeff Leek, Rohan Jeremiah, Jeremy Gooks and our faculty member Candace Savanan is responsible for a lot of the work that I'll show today as well as myself. Next slide. And you may recognize some other previous members Sarah Whelan and Karim Watson. Next slide. Okay, so one of the major things that we wanted to do was reach the widest audience possible. And next slide. We also wanted to allow others to create content that they could spread as wide an audience as possible. Next slide. We also wanted to make the material that we created easy to update because as technology changes rapidly we wanna make sure that the education content is up to date. Next slide. And we also wanted to make it easy for others to do the same. Next slide. And so this first open source tools for training resources or Otter which you can find at otterproject.org which is our software and tools to help us publish data science education. Next slide. And so the main idea here is that you can write your content once and you can publish it three times three different ways. And so the first way would be book down which many of us are familiar with has very low barrier of access. It's essentially a website. But the problem here is that users don't really have an ability to get certification. Whereas Lean Pub which is sort of a technology education platform allows for this and also allows for us to sort of specify how much a user would pay. They themselves can choose to take a course for free or to give a particular amount that they choose. And then Coursera is typically accessed by users who pay a membership fee. And this also allows for a certificate of completion and has a very, very large user base of 82 million registered users. Next slide. And so the main way that this works is we have an R Markdown currently that then creates a book down website, a Lean Pub course and or Coursera course. And there are some setup pieces required for Lean Pub and Coursera involving some copy and paste for Coursera. But for the large part, once everything is set up all updates can be made automatically. Next slide. And so this is really a collection of resources. It involves templates on GitHub, which rely on GitHub actions, Docker image, so that people don't have to load the packages, YAML configuration files, book down R Markdown currently, although we tested out using Corto and hope to go in that direction soon. We also have some packages, Otter Pal and Cow that help work with Otter template. And we have guides at the OtterProject.org. Next slide. But really you don't need to know about the back end information unless you're interested in it. So to actually use our resources you would just go to our repository for the template and click the use this template button and follow the guide at our OtterProject.org website. Next slide. And so there's a YAML file for configuring what checks one might want to run and users can simply specify no or yes and can specify what publishing platforms they'd like to use, as well as what Docker image they'd like to use if they'd like to use their own. Next slide. And so ultimately this results in a lot of checking opportunities, their spell check, check for broken URLs, rendering of material, collecting images from Google slides which is where we keep ours, conversion of formatting so that it works for all of these platforms and this includes also for quizzes. Next slide. And if you're interested, what packages we're using in large part for most of these checks, that information is here as well. Next slide. And so we have two basic method levels for writing. We have an entry level that allows people to use our tools with limited GitHub knowledge and provides more of a GUI system that's basically editing documents directly on GitHub and for advanced users, there's more flexibility in a different workflow for those who are experienced with GitHub. Next slide. But really Otter requires pull requests which we know is not super intuitive necessarily for beginners for GitHub but we have a lot of reason for this. Next slide. So our motivation is ultimately to pull requests save time long term. So we think that it encourages collaboration and feedback. It adds an extra safety net to make sure that mistakes don't happen, particularly when we already have our courses published in three different places and we're updating them and pushing them smoothly. We wanna make sure that things are correct. And it also really encourages transparency and although it requires more time and effort in the short term, overall we find that it's much quicker long term. Next slide. And so by using pull requests, we can use GitHub actions and if you were to submit a pull request using our template, you would see rendering of a preview from the book down version, the Coursera and Lean Pub version as well as a docs version which can be really helpful for getting feedback from our experience. Next slide. And the checks that you would see in submitting a pull request would look something like this. And if you happen to decide to skip a particular check like the Lean Pub quiz check, you would see that it was skipped. And if anything failed, you would have a link directly to see what failed. Next slide. And so if you recall, we wanted to make updates really easy for ourselves and for others to make because we know that this is really important for rapidly changing materials. Next slide. And so the typical manual process that we used to use because we published a lot of courses on Lean Pub and Coursera is very slow and very error prone. And so the audit process is just much, much more automated and provides all these checks for spelling and broken URLs that's just very, very helpful. Next slide. And we have several classes that use Otter. There are many more outside of ITN, but within ITN, we have one about leadership for cancer informatics research, which is basically management practices within the lab to support informatics trainees, computing for cancer informatics, documentation and usability for those who are developing tools and want to make them more usable, introduction and advanced reproducibility classes, as well as a couple of classes that are coming together now, one about ethical data handling and how to choose genomics tools. Next slide. And so just with that, I'd like to make a plug that if any of this is interesting to you and you'd like to work with us, we're looking for a programmer. So please check out our website and let us know. Next slide. Thanks and I'll take any questions. Appreciate your patience.