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Last active May 16, 2020

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RxRx19a README

RxRx19a

For more information about RxRx19a please visit RxRx.ai and read the asscociated paper, Identification of potential treatments for COVID-19 through artificial intelligence-enabled phenomic analysis of human cells infected with SARS-CoV-2.

RxRx19a was produced by Recursion and is part of a larger set of datasets than can be found at RxRx.ai.

Metadata

The metadata can be found in metadata.csv and downloaded from here. The schema of the metadata is as follows:

Attribute Description
site_id Unique identifier of a given site
well_id Unique identifier of a given well
cell_type Cell type tested
experiment Experiment identifier
plate Plate number within the experiment
well Location on the plate
site Indication of the location in the well where image was taken (1, 2, 3 or 4)
disease_condition The disease condition tested in the well (mock, irradiated or viral)
treatment Compound tested in the well
treatment_conc Compound concentration tested (in uM)

Images

The images are found in images/* and can be downloaded from here (n.b. this is 445GB). The image data are 1024x1024 8-bit png files. The image paths, such as HRCE-1/Plate1/AA02_s2_w3.png, can be read as:

Experiment Name: Cell type and experiment number (HRCE experiment 1)
Plate Number (1)
Well location on plate (column AA, row 2)
Site (2)
Channel (3)

All five channels (w1 - w5) make up an single image of a given site.

Deep Learning Embeddings

The deep learning embeddings can be found in embeddings.csv and downloaded from here (n.b. this is 1.4GB).

Each row in the csv has a site_id as described in the metadata schema. The remaining 1024 columns is the embedding for that respective site.

License

Creative Commons License

This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.

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