Teaching and Mentoring Interests

Teaching and education is one of my passions. I spend a lot of time developing coursework/workshops in a variety of Data Science Topics. Most of my material is freely available to be reused by other instructors.

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). This is a super fun course for me to teach and it focuses on both organizational behavior and communicating analytic results. It is a great blend of practical soft skills in communication and hard analytic skills.

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.

I was course co-director for HSMP410/PHE427 Introduction to Health Informatics at Portland State University. Spring Quarter, 2017-2018.

Other Teaching Interests

  • I am an RStudio Certified Instructor in the tidyverse. I’m happy to consult with groups wanting to think about building a training program in RStudio/R for their group.
  • I am also a Certified Instructor for the Carpentries, a volunteer based group that trains researchers in computing skills and have contributed to lesson materials there.
  • BioData Club - I am a co-founder and faculty co-advisor (along with Robin Champieux) for 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 am now a co-organizer in the PDX R User Group and I was one of the organizers of the first Cascadia R conference.

Teaching Materials

Click the titles to see the teaching materials. Feel free to reuse, fork, and contribute! There are more teaching materials available on my CV page.

R Bootcamp

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 and runs off the Binder cloud service. Written with Jessica Minnier.

Data Scavenger Hunt: NHANES

An introduction to Exploratory Data Analysis using the burro app to explore outcomes using the NHANES (National Health and Nutrition Examination Survey) dataset. With Jessica Minnier and Thomas Frohwein.

A gRadual intRoduction to Shiny

A workshop that I’ve given on the basics of building Shiny apps. Given multiple times for PDX R User Group.

A gRadual intRoduction to the tidyverse

A workshop that Chester Ismay and I gave for Cascadia-R teaching the basics of the tidyverse: ggplot2, dplyr, and tidyr.

Cardiovascular Risk Workshop

A workshop given for Portland State University students exploring the difficulties of predicting cardiovascular risk using shiny for exploratory data analysis and caret for machine learning. Part 1 and Part 2. With David Dorr

Clinical Data Wrangling Workshop

10 hour/multi-day workshop on understanding clinical data quality issues through both didactic lecturing and active data exploration. With Eilis Boudreau and Nicole Weiskopf. DOI

Data Analytics

Practical coursework in R/SQL for our hybrid Data Analytics Course taught with Kaiser Permanente. This course has been taught from 2013 to the present during summer quarter for students in the Biomedical Informatics program at OHSU..

Exacloud Tutorial

Self paced tutorial for learning about cluster computing using exacloud, the exascale computing cluster at OHSU. Covers simple jobs, batch jobs, and interactive jobs using SLURM.

Health Informatics

Course material I have been developing for PHE427, Health Informatics. This is a course that is co-taught with Bill Hersh for the OHSU/PSU School of Public Health. They are intended for students with very little math and programming background. Where possible, I’ve tried to have hands-on activities for each of the subjects.

Introduction to Categorical Data Analysis

LearnR tutorial for the OHSU Data Science Institute introducing students to concepts of categorical data analysis. Part of the DSIExplore package authored with Jessica Minnier.

Introduction to Github Pages

A pain free introduction to getting a personal academic website started using GitHub pages. With Robin Champieux, Eric Earl, and Eric Leung.

Introduction to igraph

Introductory workshop to the igraph package in R

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.

The Magic of Markdown

An introduction to the many uses of Markdown, including RMarkdown for reproducible scripting.

Shiny Apps

I love using the shiny app framework for both data exploration in research and teaching. Click any of these links to go to the app.

Flow Dashboard Demo

A Sample App built with the flowDashboard Shiny Modules package. Meant for visualization of high throughput flow cytometry data. Repo

NHANES explorer

A Depression focused shiny app for the NHANES (National Health and Nutrition Examination Survey) dataset. Built with burro.

Introduction to Interactive Visualization

RMarkdown/Shiny slides introducion for our BMI 569669 Data Analytics course to interactive visualizations.

Introduction to Data Literacy

LearnR Tutorial introducing our HSMP Health Informatics Class to data literacy concepts. Based on a great LearnR tutorial from Mikhail Popov. Repo

Decision Tree Explorer

Simple Shiny App to explore decision tree building with the party paackage. Repo

Introduction to Categorical Data Analysis

LearnR tutorial for the OHSU Data Science Institute introducing students to concepts of categorical data analysis. Part of the DSIExplore package authored with Jessica Minnier.

A Visual Introduction to Clustering Algorithms

Interactive slides with apps to explore properties of clustering algorithms. Built with RMarkdown/Shiny

Surrogate Oncogene Explorer

One of my first shiny apps. Heatmap interface to explore the network effect of gene alterations on networked oncogene signatures. Repo

Recent Posts

More Posts

In healthy cultures, people rise by elevating others and fall by undermining others. In toxic cultures, people are forced to choose between helping others and achieving success. Choose the workplace where success comes from making others successful. - Adam Grant When I read Adam Grant’s Give and Take, it was like a light went off. In this book, Grant gives profiles of highly successful people who are givers - people who have changed their field by making things better for others.

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Last year about this time, I had a meltdown, which is a symptom of burnout. I’d like to explain a little bit about my burnout in the hopes that other people can avoid it. I want to help people, and I’m a people pleaser. I’m a giver, and sometimes I give too much, to the point I have nothing left. I have to be aware when people exploit this. One collaboration, unfortunately took advantage of my giving nature.

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As part of my new year’s resolution to learn new things about R, I’m trying to plug some holes in my R knowledge by writing more vignettes to explain them to myself this year. This week I finally think I understand more about namespaces in R and why you should use them in your R package. Namespaces: Why Bother? In short, we need namespaces because of the ambiguity of function names.

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Well, RStudio Conf 2019 has come and gone. I attended the main conference, starting with the poster session on wednesday and stayed through the tidyverse developer day on Saturday. To say that the conference was inspiring was an understatement. So many talented people working on such interesting and inspiring packages! It made me excited again about doing data science and teaching data science. This post is going to highlight the interesting talks about education and organizational management at the conference.

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At some point in your life in Data Science, you will probably struggle with impostor syndrome. We all do - in fact, even though I have used R and have done bioinformatics and data science for more than 15 years, I still struggle with this feeling. As a beginner, the mountain you must climb to master skills in data science seems like a long and impossible one. Caitlin Hudon, in her post about dealing with impostor syndrome has this to say about countering impostor syndrome:

CONTINUE READING

Software

  • burro. R Package for building data exploration apps for Data Scavenger hunts. With Jessica Minnier and Gabrielle Choonoo. DOI
  • 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 Publications

More Publications

. CSF1R inhibitors exhibit anti-tumor activity in acute myeloid leukemia by blocking paracrine signals from support cells. Blood, 2018.

PDF

. Immunogenomic Exploration of the Acute Myeloid Leukemia Microenvironment Identifies Determinants of T-Cell Fitness. Blood, 2018.

. Integrated functional and mass spectrometry-based flow cytometric phenotyping to describe the immune microenvironment in acute myeloid leukemia. Journal of immunological methods, 2018.

Code

. Teaching data science fundamentals through realistic synthetic clinical cardiovascular data. bioRxiv, 2018.

Preprint Code Dataset

. Comprehensive characterization of VISTA expression in patients with acute myeloid leukemia.. Journal of Clinical Oncology, 2016.

. Enhanced VISTA expression in a subset of patients with acute myeloid leukemia. Blood, 2016.

. Mass cytometry as a modality to identify candidates for immune checkpoint inhibitor therapy within acute myeloid leukemia. Blood, 2016.

. A network-based model of oncogenic collaboration for prediction of drug sensitivity. Frontiers in genetics, 2015.

PDF Code Poster

. Between pathways and networks lies context: implications for precision medicine. Science progress, 2015.

PDF

. Consensus molecular subtyping through a community of experts advances unsupervised gene expression-based disease classification and facilitates clinical translation. Cancer Research, 2015.

Contact

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.

Frequently Asked Questions

What are your priorities?

In order, they are:

  1. My mental and physical health
  2. My students
  3. Open Science and creating a positive working environment for myself and others
  4. Making and promoting new educational resources
  5. Enabling better research practices

What do I need to know about working with you?

I am clinically depressed and have anxiety, but I am high-functioning. I do my best to meet deadlines, but sometimes there is a lot on my plate and I need to manage my anxiety and depression.

The number one thing to know is that last minute deadlines are a significant stress on my anxiety and affect me very negatively. I realize that this is the more often the case than not with grant deadlines, but the sooner you can ask for something before its deadline, the better.

These are hard deadlines for collaborating with me:

  • 1 week notice (at least): Minor edits on figures
  • 2 week notice (at least): New Figures based on existing data analysis
  • 4 weeks notice (at least): New analysis based on your data that I haven’t seen.

If you don’t like these deadlines, there are other people out there who will probably work with you.

I do best when there is mutual respect between me and my collaborators. Good collaborations take time and I have to learn to trust working with you.

I’m a Student and I want to work with you. How can I do this?

Email me and we’ll set up an appointment to talk. If you are interested in what I’m interested in (see above), I will see if we can set up some sort of internship.

I’d like to collaborate with you on a project

Email me and we’ll set up a time to talk. Note that I have been burned pretty badly in the past, so our goals have to align or we might have to negotiate a contract and scope of work.

What if I really need things at the last minute?

You get one of these a year. I’ll print you a coupon. You cannot get more. I value my own mental health more than responding on the weekends. Be respectful.

Please do not try to send me an appointment for the current time and expect to talk. I’m not going to respond. I feel this is disrespectful, and I don’t have the patience or energy to do so.