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Dose response curves and DIP rates for cell proliferation data in Python

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Thunor

Thunor (pronounced THOO-nor) is a free software platform for managing, visualizing, and analyzing high throughput screen (HTS) data, which measure the dose-dependent response of cells to one or more drug(s). Thunor has a web interface for drag-and-drop upload of cell count data, automatic calculation of dose response curves, and an interactive multi-panelled plot system.

This repository, Thunor Core, is a Python package which can be used for standalone analysis or integration into computational pipelines. There is also a web interface, Thunor Web, built around this package with added database and multi-user capabilities.

Implementation

Thunor is written in pure Python and is compatible with Python 3 only. It makes extensive use of pandas and plotly.

Installation

Install using pip:

pip install thunor

Examples and documentation

The Thunor Core documentation is available online, or you can build it locally for offline use. To do so, clone this git repository and change into the thunor directory.

To build documentation locally, you'll need a few software dependencies:

pip install -r doc/requirements.txt

Then, you can build the documentation like so:

cd doc
make html

After the build completes, open _build/html/index.html in your web browser.

Tutorial

To manually work through the tutorial from the documentation above, you can open the file with Jupyter Notebook:

jupyter notebook --NotebookApp.iopub_data_rate_limit=1.0e10 doc/tutorial.ipynb

Citation

Lubbock A.L.R., Harris L.A., Quaranta V., Tyson D.R., Lopez C.F. Thunor: visualization and analysis of high-throughput dose–response datasets Nucleic Acids Research (2021), gkab424.

Further help and resources

See the Thunor website for further links, documentation and related projects.

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Dose response curves and DIP rates for cell proliferation data in Python

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