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RxRx1 is the first dataset released by Recursion in the series and was the topic of the NeurIPS 2019 CellSignal competition. It contains 125,510 images of 6-channel fluorescent cellular microscopy, taken from four kinds of cells perturbed by 1,138 siRNAs. The goal of the competition was to train models that could identify which siRNA was used in a given image taken from an experimental batch not seen in the training data. For more information about RxRx1 please visit

RxRx1 is part of a larger set of Recursion datasets that can be found at and on GitHub. For questions about this dataset and others please email


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
dataset The split that this site belongs to; train or test
experiment The experiment name, same as explained above
plate Plate number within the experiment
well Location on the plate
site Indication of the location in the well where image was taken (1 or 2)
well_type Indicates if the well is a treatment, negative_control, or positive_control
sirna The siRNA (ThermoFisher ID) that was introduced into the well
sirna_id The siRNAs mapped to integers for ease of classification tasks


The images are found in images/* and can be downloaded from here (n.b this is 47GB). The images are 512x512 8-bit png files. The image paths, such as HUVEC-1/Plate1/M23_s2_w3.png, can be read as:

  • Experiment Name: Cell type and experiment number (HUVEC experiment 1)
  • Plate Number: 1
  • Well location on plate: column M, row 23
  • Site: 2
  • Channel: 3

All six channels (w1 - w6) make up a single image of a given site.


  • June 2019: original release for CellSignal; train images only
  • December 2019: updated to include test images after completion of CellSignal competition
  • August 2020: file organization updated and license changed to CC-BY-NC-SA


Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. To view a copy of this license, visit or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.