Welcome to the Simplicity web app!

This app was created to provide simple, non-programmatic access to explore and perform calculations with data from high-throughput cancer drug screens performed in cancer cell lines. Each of the included datasets (CTRPv2, GDSC1, GDSC2, and PRISM-Repurposing) have screened hundreds of compounds in hundreds of cell lines.

You can watch this video for a quick tutorial on using Simplicity. Otherwise, please feel free to get started by selecting the appropriate tab at the top for the task you wish to complete. The basic functions of each tab are as follows:

Data Explorer
  • Explore Datasets: Provides a birds-eye overview of the compounds, cell lines, screening methodologies, and data quality associated with each of the datasets included in Simplicity.
  • Explore Compounds: Easily visualize the effectiveness of a compound across a custom set of cell lines in each dataset. Also allows you to see the characteristics (i.e. age, gender, ethnicity) of the cell lines tested with each compound in each dataset.
  • Explore Cell Lines: Easily visualize the response of a cell line to a custom set of compounds in each dataset.
  • Plot Dose-Respone Curves: A detailed look at single compound-cell line pairs. View raw data, fitted dose-response curves, and experimental details from each dataset for the selected pair.

Calculate Custom Statistics
  • AUC Values: Calculate normalized area under the curve (AUC) values from each dataset using custom concentration ranges for each compound.
  • Viability Values: Calculate viability values from each dataset using custom concentration ranges for each compound. Can be used to generate custom inputs for our IDACombo-shiny app.

About Simplicity
  • Methods: Details about how the data in Simplicity was generated.
  • Contact Us: Who we are and how to get in touch with us.
  • Cite This Resource: If you use this resource for your research, please cite us and the researchers who generated the data in Simplicity when you publish your work! This tab contains information on how to do that.
  • Usage License: If you download any data from any tabs in Simplicity, please read this to learn about what you can and cannot do with that data.

Download Bulk Data: Where to go if you want to download the data being used by this app.

Dataset Explorer

This page provides a birds-eye overview of each of the datasets included in Simplicity. You can change which dataset is being summarized using the drop-down menu below.

By following the instructions below, this tab can be used to calculate normalized area under the curve (AUC) values (see methods tab) for custom concentration ranges using the fitted dose-response curves in Simplicity for each dataset.

Step 1: Select a dataset to use for AUC calculations.

Step 2 (optional): Generate a template instruction file which can be downloaded and modified to specify the compounds and concentration ranges to be used for AUC calculations.

Step 3: Upload an instruction file specifying the compounds and concentration ranges to be used for AUC calculations.

Step 4: Select the cell lines for which AUC are to be calculated for the compounds/concentration ranges specified in the instruction file.

Step 5: Press "Calculate AUC Values" button to generate and download calculated AUC values.

By following the instructions below, this tab can be used to calculate cell line viability values (see methods tab) at custom compound concentrations using the fitted dose-response curves in Simplicity for each dataset.

Step 1: Select a dataset to use for viability calculations.

Step 2 (optional): Generate a template instruction file which can be downloaded and modified to specify the compounds and concentrations to be used for viability calculations.

Step 3: Upload an instruction file specifying the compounds and concentration ranges to be used for Viability calculations.

Step 4: Select the cell lines for which viability values are to be calculated for the compounds/concentrations specified in the instruction file.

Step 5: Press "Calculate Viability Values" button to generate and download calculated viability values.

Note that pre-calculated viability values and standard errors are available for download at select concentrations for all compounds/cell lines. These can be accessed in the "Download Bulk Data" tab.

Please feel free to contact us!

We would love to answer any questions you have about Simplicity. We also want to hear about any bugs you encounter when using the app or any features you would like us to add so we can keep improving Simplicity's usefullness to the field.


Principal Investigator:

R. Stephanie Huang (rshuang@umn.edu)


App Author:

Alexander Ling (Alexander.L.Ling@gmail.com)

If you use this resource for your research, please cite us, along with the original creators of any datasets you use from Simplicity.

Simplicity App:

Xia, Y., Ling, A. L., Zhang, W., Lee, A., Su, M. C., Gruener, R. F., Jena, S., Huang, Y., Pareek, S., Shan, Y., & Huang, R. S. (2024). A Web Application for Predicting Drug Combination Efficacy Using Monotherapy Data and IDACombo. Journal of cancer science and clinical therapeutics, 7(4), 253–258.

Compound and Cell Line Harmonization Tables and Csustained values:

1. Ling, A. & Huang, R. S. Computationally predicting clinical drug combination efficacy with cancer cell line screens and independent drug action. Nat. Commun. 11, 1–13 (2020).

CTRPv2:

1. Basu, A. et al. An Interactive Resource to Identify Cancer Genetic and Lineage Dependencies Targeted by Small Molecules. Cell 154, 1151–1161 (2013).

2. Seashore-Ludlow, B. et al. Harnessing Connectivity in a Large-Scale Small-Molecule Sensitivity Dataset. Cancer Discov. 5, 1210–1223 (2015).

3. Rees, M. G. et al. Correlating chemical sensitivity and basal gene expression reveals mechanism of action. Nat. Chem. Biol. 12, 109–116 (2016).

Visit their website at https://portals.broadinstitute.org/ctrp/.

GDSC1 and GDSC2:

1. Iorio, F. et al. A Landscape of Pharmacogenomic Interactions in Cancer. Cell 166, 740–754 (2016).

2. Yang, W. et al. Genomics of Drug Sensitivity in Cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells. Nucleic Acids Res. 41, D955–D961 (2013).

3. Garnett, M. J. et al. Systematic identification of genomic markers of drug sensitivity in cancer cells. Nature 483, 570–575 (2012).

Visit their website at https://www.cancerrxgene.org/.

PRISM-Repurposing:

1. Corsello, S. M. et al. Discovering the anti-cancer potential of non-oncology drugs by systematic viability profiling. Nat. Cancer 1, 235–248 (2020).

Visit their website at https://depmap.org/repurposing/.

Usage of GDSC1 and/or GDSC2 Data:

Users have a non-exclusive, non-transferable right to use data files for internal proprietary research and educational purposes, including target, biomarker and drug discovery. Excluded from this licence are use of the data (in whole or any significant part) for resale either alone or in combination with additional data/product offerings, or for provision of commercial services.

Users must also cite the appropriate references for the used datset(s) as specified in the "About Simplicity/Cite This Resource" tab.

Usage of CTRPv2 and PRISM-Repurposing Data:

Users must respect the original licences under which these resources were released as well as cite the appropriate references for the used dataset(s) as specified in in the "About Simplicity/Cite This Resource" tab.

CTRPv2 website: https://portals.broadinstitute.org/ctrp/.

PRISM-Repurposing website: https://depmap.org/repurposing/.

Download the bulk data used by Simplicity.

This page contains links to download the bulk data used by Simplicity. Please don't forget to visit the "About Simplicity/Cite This Resource" tab to find out how to cite Simplicity and the original creators of the data used by the app.

By downloading this data, you agree to abide by the usage guidelines posted in the "About Simplicity/Usage License" tab.

Harmonization Tables:

Harmonized_CCL_Data_v1.0.xlsx: An excel spreadsheet containing information about each of the cell lines used by each dataset, along with harmonized identifiers for each cell line and the names originally used by each dataset.

Harmonized_Compound_Data_v1.0.xlsx: An excel spreadsheet containing information about each of the compounds used by each dataset, along with harmonized identifiers for each compound and the names originally used by each dataset.

Csustained Values:

Csustained_v1.0.xlsx: An excel spreadsheet containing information about the clinically sustainable plasma concentrations (Csustained) for clinical compounds included in Simplicity. Please see the "About Simplicity/Methods" tab for details about how Csustained values are determined.

Dataset Summary Results:

CTRPv2_Results_v1.0.tsv: A tab-separated value text file containing curve parameters, tested concentrations, AUC values, and IC50 values for the compound-cell line pairs tested in CTRPv2.

GDSC1_Results_v1.0.tsv: A tab-separated value text file containing curve parameters, tested concentrations, AUC values, and IC50 values for the compound-cell line pairs tested in GDSC1.

GDSC2_Results_v1.0.tsv: A tab-separated value text file containing curve parameters, tested concentrations, AUC values, and IC50 values for the compound-cell line pairs tested in GDSC2.

PRISM_Repurposing_Results_v1.0.tsv: A tab-separated value text file containing curve parameters, tested concentrations, AUC values, and IC50 values for the compound-cell line pairs tested in PRISM_Repurposing.

Pre-Calculated Viability Values:

Zipped .tsv files with pre-calculated viability values and standard error estimates for all compounds/cell lines in each dataset. Viabilities are calculated at 11 concentrations from 0 to the most commonly used maximum concentration tested for each compound. An additional 11 concentrations are provided from 0 to Csustained if Csustained is available for a compound and Csustained is not greater than the most commonly used maximum tested concentration for that compound in that dataset.

CTRPv2_Calculated_Viabilities.zip

GDSC1_Calculated_Viabilities.zip

GDSC2_Calculated_Viabilities.zip

PRISM_Repurposing_Calculated_Viabilities.zip

Dataset Raw Data:

CTRPv2_Results_v1.0.tsv.7z: A 7-zip compressed, tab-separated value text file containing the raw data from CTRPv2 after compound and cell line name harmonization.

GDSC1_Results_v1.0.tsv.7z: A 7-zip compressed, tab-separated value text file containing the raw data from GDSC1 after compound and cell line name harmonization.

GDSC2_Results_v1.0.tsv.7z: A 7-zip compressed, tab-separated value text file containing the raw data from GDSC2 after compound and cell line name harmonization.

PRISM_Repurposing_Results_v1.0.tsv.7z: A 7-zip compressed, tab-separated value text file containing the raw data from PRISM_Repurposing after compound and cell line name harmonization.

Dataset Full Curves:

The drc fit objects with full statistical information for each of the fitted curves in Simplicity can be downloaded from the OSF repository for this project.