Teaching and Mentoring Interests

Current Courses I teach at OHSU and PSU

I teach in the summer hybrid BMI569/669 Data Analytics course at OHSU (Hybrid course co-taught with Kaiser Permanente Data & Information Management Enhancement (DIME) group).

I am also a co-instructor for BMI551/651 Bioinformatics and Computational Biology II: Statistical Methods, providing drop-in sessions for R programming and general tutoring.

We are teaching an introductory bootcamp in Python called NEU640 Python Bootcamp for Neuroscientists.. This is a week-long course meant to introduce neuroscience students to the basics of python with data types familiar to them, including imaging and electrophysiology data. Taught with Stephen David, Brad Buran, Daniela Sadieri, Lucille Moore, Charlie Heller, Zack Schwartz. Winter Quarter, 2018.

I am also course co-director for HSMP/PHE410 Introduction to Health Informatics. at Portland State University. Spring Quarter, 2018.


I have a free online introductory course at DataCamp called the RBootcamp. In this course, we cover the basics of visualization, data munging, and basic statistics using the tidyverse in R. It is freely available to everyone, but registration is required.

I am currently developing a course called Statistical Analysis of Networks in R for DataCamp. More info as it develops.

Training Materials/Workshops

I have developed a number of self-directed training materials for learning R and specific packages that I’ve found useful. Most of these are available from my github page and may be used freely by students.

  • R-Bootcamp (tidyverse) - The new version of RBootcamp, that covers the tidyverse for manipulating data in R. You will need to register on DataCamp. This interactive course was written with both Jessica Minnier and Chester Ismay. DOI
  • R-Bootcamp (Base R) - an MOOC (Massively Open Online Course) for teaching the basics of data manipulation in R (Coursesites registration required). Note that I do not support this course anymore at this point.

Standalone Tutorials

Many of these tutorials have been given through the student club at OHSU that I mentor, called BioData Club. They are all freely available to be reused by other instructors.

  • The Magic of Markdown - An introduction to the many uses of Markdown, including RMarkdown for reproducible scripting.
  • GitHub Pages - A pain free introduction to getting a personal website started using GitHub pages. With Robin Champieux and Eric Leung.

R Tutorials

As a developer and programmer of R, I enjoy teaching others about the basics of data wrangling and analysis. Here are a few of the tutorials I’ve put together.

Big Data to Knowledge

As an instructor under OHSU’s Big Data To Knowledge (BD2K) Training Grant, I have also developed the following short workshops to encourage students to explore data and learn the basics of data-wrangling.

Other Teaching Interests

  • BioData Club - A student and postdoc driven discussion group at OHSU that focuses on practical skills (documentation, software engineering and visualization) necessary for success in data science and bioinformatics.
  • I participate in the PDX R User Group and I was one of the organizers of the first Cascadia R conference
  • I have also started to contribute lesson material to Software Carpentry.

Recent Posts

More Posts

This term, I’m co-teaching an undergraduate course for the PSU/OHSU School of Public Health called Health Informatics with a number of my collegues in my department, including Bill Hersh, Eilis Boudreau, Karen Eden, and Virginia Lankes. We’re trying to give students a feel for what informatics is about in an accessible way. I’m trying to make the lectures as understandable as I can. This week we tackled Genome Wide Association Studies and discussed the strength of evidence behind SNP variants associated with phenotypes.


Last week I had the good fortune to attend the From Evidence to Scholarship Conference at my alma mater, Reed College. The focus of the conference was improving the research process for undergraduates using digital scholarship. I came away from it excited about the work other people are doing in this realm and thinking about ways we could adapt these approaches. Nicole Vasilevsky and I (both former Reedies) each gave talks, about our experience developing materials for Data Science and giving data science workshops to undergraduates.


I gave a talk for the Portland State University Systems Science seminar called How are Data Science and Systems Science Connected?. In this talk, I was highlighting current blind spots in Data Science that I think Systems Science approaches can address, especially that of interactions between features. I talked a little about my dissertation research (surrogate oncogenes), and the problem of black-box interpretability of predictive models. If you’re interested in listening to the recording, the playback is available here: https://us.


I just gave a workshop teaching the basics of Shiny (the interactive web visualization framework) for a group of PDX R users. We had 10 people attend, and most of the attendees managed to get through the material and had lots of good questions. I really enjoyed talking with everyone and I hope everyone learned something. We’re planning to give the workshop again to the larger PDX R user community, and some of the attendees last night have volunteered to be TAs.


Well, the week of teaching our Python Bootcamp for Neuroscientists is over. I had the pleasure of working with a great group of students, professors and instructors in developing the material, and had a great time teaching complete beginners to programming and Python. We had the overall goal of introducting 21 Neuroscience Graduate Program students at OHSU to the basics of programming in Python using data that they were interested in: electrophysiology data, and confocal microscopy data.



  • flowDashboard. Shiny modules for building interactive and comparative dashboards for flow cytometry data. See a demo here: https://tladeras.shinyapps.io/sampleFlowDashboard/ DOI
  • DSIExplore. Interactive learnr package for teaching beginning exploratory data analysis and statistics. Jessica Minnier and Ted Laderas. Role: author.
  • infer. Tidy statistical inference package. Andrew Bray, Chester Ismay, Ben Baumer, Mine Cetinkaya-Rundel, Ted Laderas and Nick Solomon. Role: Contributor.
  • surrogateMutation - a package for detecting oncogenic collaboration in somatic mutation and copy number data. DOI
  • surrogateShiny - an R/Shiny Framework for exploring oncogenic collaboration in breast cancer cell lines. See a demo here: https://tladeras.shinyapps.io/surrogateShiny/ DOI
  • Consense - a package for comparing clustering methods. DOI
  • ExonModelStrain - a package for detecting alternative exon usage in the Affymetrix Exon Array. DOI
  • TandTRAQ - Perl Script for merging iTRAQ and XTandem Results.

Recent & Upcoming Talks

Selected Publications


Other Interests

I have a parallel career as a composer and performing musician. I started taking cello lessons when I turned 30. I’m a lifelong learner and I love to play with and accompany other musicians. For more information, please see my artist webpage.