Explore the Cancer Dependency Map

Welcome to the DepMap Portal!

The goal of the Dependency Map (DepMap) portal is to empower the research community to make discoveries related to cancer vulnerabilities by providing open access to key cancer dependencies analytical and visualization tools.

Use this portal to:

DISCOVER genetic and pharmacological dependencies

SOX10 gene dependency overview

Dabrafenib compound overview

EXPLORE over 2000 cancer models

UACC62 Cancer model overview

BROWSE and download the latest datasets

Visit Data Downloads

Share your comments, request features or report a bug on the DepMap Community Forum

Call for Cancer Cell Models

We wouldn’t be able to build DepMap without the help of the many collaborators and partners who have already shared their cell lines and organoids.

If you are interested in identifying cancer vulnerabilities in your favorite models, please consider sharing them and allowing us to generate data which will be available to the entire community.


May 12, 2020
March 30, 2020
  • Want tips on how to think about DepMap data? Interested in knowing more about the decisions that go into the portal? CDS is launching its official blog to address this and more. Check it out at https://cancerdatascience.org/blog/.

Feb 6, 2020
Jan 21, 2020
  • Drug Repurposing data from Corsello, Nature Cancer (2020) now out, and fully incorporated in Data Explorer and explorable on the Dose Curves tab! Download the data here or explore the data on the paper landing page

New features and data updated quarterly

This portal enables analysis of data generated at the Broad Institute jointly with data generated elsewhere including:

As part of our commitment to Open Science, we make all the Broad Institute data generated by the DepMap Project rapidly available to the public under the permissive CC BY 4.0 license on a quarterly basis and prepublication.

Because this portal also hosts data not generated by the Broad Institute DepMap Project, please be sure to review the data policy for each dataset prior to use.