Accelerating the Pace of Childhood Cancer Research with Big Data

Alex's Lemonade Stand Foundation Logo

The Childhood Cancer Data Lab was established by Alex’s Lemonade Stand Foundation (ALSF) in 2017. ALSF recognized that pediatric cancer researchers face hurdles that impede the pace of research. 

ALSF introduced the Data Lab to empower researchers and scientists across the globe by removing roadblocks, supporting opportunities for collaboration and sharing, and developing resources to accelerate new treatment and cure discovery.

The Data Lab's mission is to empower pediatric cancer experts poised for the next big discovery with the knowledge, data, and tools to reach it. We construct tools that make vast amounts of data widely available, easily mineable, and broadly reusable. We train researchers and scientists to better understand their own data and to advance their work more quickly.

To date, the Data Lab has trained over 200 childhood cancer researchers and has harmonized over 1.3 million data samples and made them easily available. Learn more about the Data Lab’s impact here. 

Two people looking at goals

Projects

The Data Lab develops tools designed to make data and analysis widely available and broadly reusable.

Data Science Workshops

The Data Lab offers workshops to teach researchers the data science skills they need to examine their own data. Our courses focus on the most cutting edge tools and analysis techniques. We ensure that participants walk away with an understanding of:

  • The R programming language, R Notebooks, and some reproducible research practices.
  • Processing bulk and single-cell RNA-seq data from raw all the way to downstream analyses.
  • Downstream analyses methods like differential expression analyses, hierarchical clustering, and preparing publication-ready plots.

“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

Donate

Make a donation to support the Data Lab’s mission of putting knowledge and resources in the hands of pediatric cancer experts poised for the next big discovery. 

With your help, we can

Fund innovative models to scale training workshops.

Offer our expertise and provide consultation on projects that will change the future for children fighting cancer.

Train at least 200 childhood cancer researchers over the next four years.

Blog

Projects

November 11, 2024

Projects
2024-11-11
Building reproducible workflows for testing and reproducible results in OpenScPCA

In our last blog post, we shared some of the tools and methods we are using in the Open Single-cell Pediatric Cancer Atlas (OpenScPCA) project to ensure that the analysis code remains usable and runnable throughout the project. That post mainly focused on some of the most dynamic phases of the project, when contributors are adding new analysis modules and updating existing ones with more refined results. Here, we will discuss the test data that enables the methods and our approach to running the full set of analyses on real data.

JOSHUA SHAPIRO

Announcements

October 28, 2024

Announcements
2024-10-28
Full: Data Lab Advanced Single-cell RNA-Seq Workshop, Philadelphia area, December 10-12, 2024

Applications are open for the Data Lab's next training workshop! We will cover advanced topics in the analysis of single-cell RNA-seq data for researchers studying pediatric cancer. The 3-day course will take place December 10-12, 2024 from 9am-5pm Eastern time in Bala Cynwyd, PA, just outside of Philadelphia.

JEN O'MALLEY

Projects

September 30, 2024

Projects
2024-09-30
Working reproducibly with others on OpenScPCA

Earlier this year, we launched the Open Single-cell Pediatric Cancer Atlas (OpenScPCA) project, a collaborative project to openly analyze the data in the Single-cell Pediatric Cancer Atlas Portal on GitHub. We hope this project will bring transparently and expertly assigned cell type labels to the data in the Portal, help the community understand the strengths and limitations of applying existing single-cell methods to pediatric cancer data, and, frankly, allow us to meet more scientists in our community working with single-cell data (maybe you? 😄).

JACLYN TARONI