The DepMap portal harmonizes and integrates datasets making it easier and possible for researchers to identify genetic and pharmacological vulnerabilities in cancer models across modalities.
Data Explorer 2.0
A powerful tool built by DepMap that allows you to explore data in the DepMap portal.
Building on it’s predecessor, Data Explorer 2.0 provides more granularity around what you can plot and how you can visualize relationships. This tool can help answer questions such as, “What is the best biomarker for a given dependency?” or " Which lineage has the strongest dependency on a certain gene?".
We’ve also worked to build out more plot types, contexts and integrated other portal tools to the explorer such as GeneTea and Context Explorer. No matter how you enter the portal, you can load your view into Data Explorer 2.0 to continue your analysis.
Data Explorer 2.0 Introduction Webinar (7.31.24)
Read the tutorial
Data Explorer 2.0 Webinar
Walk through a few Data Explorer 2.0 use cases
Celligner
Helping researchers select cell lines that most closely resemble a tumor type of interest.
Although this method aligns most DepMap cell lines with tumor samples of the same cancer type, it also reveals many differences in tumor similarity across cell lines, including more mesenchymal and undifferentiated transcriptional states and that exhibit distinct chemical and genetic dependencies.
Celligner is based on an unsupervised approach that corrects for differences when integrating DepMap and tumor expression datasets (TCGA, Treehouse, and TARGET). To learn more, see the manuscript or view DepMap’s Celligner documentation.
Target Discovery
Use the Target Disvoery tool to identify novel genetic targets for cancer precision medicine based on analyses of DepMap CRISPR and RNAi datasets. Sort or filter genes by pre-computed analysis metrics, including selectivity, predictability, and biomarker class, as well as external annotations for target tractability.
