Hold a Workshop

Data Lab training materials are openly licensed and freely available for others to use to host their own workshops.

Our Training Program

Data Lab training workshops are 1-5 day in-person or virtual courses that are designed to teach pediatric cancer researchers how to better put their data to use and to introduce them to cutting-edge techniques and tools for data analysis. We have trained approximately 300 childhood cancer researchers on topics including R programming, bulk and single-cell RNA-sequencing, and reproducible research practices. Workshops feature a combination of lecture style and active learning.

Benefits of Holding a Workshop

Develop skills to increase the impact of your research
Each of our training modules introduce some reproducible research practices. Instructors and participants are exposed to processes that can help improve their ability to conduct reproducible and efficient research.

Build a community at your institution
Our workshops are designed to be interactive and participants are encouraged to ask questions, work together, and help each other. Workshops are an excellent opportunity to network, learn about your peers’ projects, and discover potential collaborators.

Connect with the Data Lab
Our team is eager to support pediatric cancer experts at all stages of their careers. We can provide assistance leading up to and during your workshop. There are plenty of ways that our data science experts can continue being a resource, even after a workshop ends.

Here’s what participants are saying!

“Before these workshops, I spent a lot of time trying to find good online resources to learn these techniques and this experience was by far the best.  My undergraduate students agree.”

Tovah Day, Assistant Professor of Biology, Northeastern University
- Tovah Day, Assistant Professor of Biology, Northeastern University

“I think anyone who is working on or near single-cell data should take this course. I am so much more confident in what I understand about single-cell analyses compared to where I was at the beginning. 10/10 recommend.”

Jessica Elswood, Postdoctoral Associate, Baylor College of Medicine
- Jessica Elswood, Postdoctoral Associate, Baylor College of Medicine

“The training was really well crafted. Instructors provided a fundamental scaffold for future R-based analyses that we can now run without necessarily needing a consolidated background as a bioinformatician.”

- Rodrigo Cartaxo, Postdoctoral Associate, University of Michigan

What We Teach and Why

The Data Lab strives to teach the most relevant and functional content and the techniques that have become most commonly used in data analysis. All of our workshops use the R programming language.

We prefer to focus on tools that:

Widely and Openly Available

  • Are widely available, open source, and cost-effective
  • Can be applied to a wide range of experimental designs
  • Have a sizeable user base

Easy to Use

  • Are easy to use, well-documented, and consistently updated
  • Have helpful tutorials and responsive authors and maintainers
  • Integrate easily into a single workflow that can be run on a laptop when possible

Our current modules include:

Intro to R and tidyverse

This course introduces the R programming language, including pipelines, and some tidyverse packages. It covers the basics of R (including data types and data structures), ggplot2 visualizations, and other tidyverse data manipulation packages and their functions.

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Bulk RNA-Seq

This course introduces the R programming language and basic downstream analysis of bulk RNA-seq data. It covers topics such as selected pipelines for quality control, how to process raw sequencing data to obtain gene expression estimates, and common approaches for pathway analysis.

View Module


This course introduces the R programming language and introduces how to process different types of scRNA-seq data and analyze them. It covers quality control, normalization, dimension reduction, clustering, cell-type annotation, and introduces working with CITE-Seq data.

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Advanced scRNA-seq

This course builds on material from the scRNA-seq module. It covers cell-type identification, integration of multiple scRNA-seq libraries, differential expression analyses and more.

View Module

Reproducible Research Practices

This course introduces concepts in reproducible computational research for genomics, including tools and approaches for organizing, managing, and sharing your code.

View Module

Hold Your Own Workshop

If you are interested in hosting your own training workshop using Data Lab materials, fill out the workshop interest form. We will contact you within 5 business days to provide additional information.

Fill out Workshop Interest Form

We may be able to provide the following support for your workshop

Onboarding Meeting

Meet with the Data Lab team for guidance while planning your workshop and to address your questions and concerns.

Guide to Obtain Training Materials

We will provide instructions for downloading the materials you need from GitHub and modifying them for your workshop.

Preparation Materials

Helpful materials such as instructor notes and recommended resources are available.

Access to Data Lab's RStudio Server

Instructors have the option to use the Data Lab's server with pre-installed tools, data, and exercise notebooks.

Observe a Data Lab Workshop

Learn more about our training program by attending a scheduled workshop as an observer.

Assistance During Your Workshop

This applies to instructors using our RStudio Server only. A Data Lab team member will be available for troubleshooting during your workshop.

Please contact us with any questions at training@ccdatalab.org