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


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


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.



January 20, 2023

Lessons learned from working reproducibly with others

In September 2022, the Open Pediatric Brain Tumor Atlas (OpenPBTA) project culminated (for now) in a preprint on bioRxiv. This project, started in late 2019 and co-organized with the Center for Data Driven Discovery in Biomedicine (D3b) at Children’s Hospital of Philadelphia (CHOP), is a collaborative effort to comprehensively describe the Pediatric Brain Tumor Atlas (PBTA), a collection of multiple data types from tens of tumor types (read more about why crowdsourcing expertise for the study of pediatric brain tumors is important here). The project is designed to allow for contributions from experts across multiple institutions. We’ve conducted analysis and drafting of the manuscript openly on the version-control platform GitHub from the project’s inception to facilitate those contributions.



January 5, 2023

A clustering analysis workflow for use with your ScPCA dataset!

Recently, we told you about the Single-cell Pediatric Cancer Atlas (ScPCA) downstream analysis workflow. This ready-to-go workflow is intended to be used with single-cell and single-nuclei gene expression data available on the ScPCA Portal. We developed this workflow to filter, normalize, and perform dimensionality reduction, as well as incorporate initial clustering results to each processed sample/library object. Now we’re excited to introduce one of our latest offerings for use with ScPCA data, a clustering analysis workflow, which can be applied to datasets after running the filtering, normalization, and dimensionality reduction workflow! 



December 1, 2022

Full: Data Lab Advanced Single-Cell RNA-Seq Workshop, Philadelphia area, January 31-February 2, 2023

The Data Lab is excited to announce that our next training workshop will be held in-person from January 31-February 2, 2023! During this 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 from 9am-5pm Eastern time in Bala Cynwyd, PA, just outside of Philadelphia. Travel reimbursement is available for qualifying participants.