| | --- |
| | dataset_info: |
| | features: |
| | - name: __key__ |
| | dtype: string |
| | - name: jp2 |
| | dtype: image |
| | splits: |
| | - name: train |
| | num_bytes: 17489993120.108 |
| | num_examples: 1335606 |
| | download_size: 17390577507 |
| | dataset_size: 17489993120.108 |
| | configs: |
| | - config_name: default |
| | data_files: |
| | - split: train |
| | path: data/train-* |
| | --- |
| | |
| | To accompany OpenPhenom, Recursion is releasing the [**RxRx3-core**](https://arxiv.org/abs/2503.20158) dataset, a challenge dataset in phenomics optimized for the research community. |
| | RxRx3-core includes labeled images of 735 genetic knockouts and 1,674 small-molecule perturbations drawn from the [RxRx3 dataset](https://www.rxrx.ai/rxrx3), |
| | image embeddings computed with [OpenPhenom](https://huggingface.co/recursionpharma/OpenPhenom), [MAE-L/8](https://arxiv.org/pdf/2404.10242), [MAE-G/8](https://arxiv.org/pdf/2411.02572), and associations between the included small molecules and genes. |
| | The dataset contains 6-channel Cell Painting images and associated embeddings from 222,601 wells but is less than 18Gb, making it incredibly accessible to the research community. |
| |
|
| | Mapping the mechanisms by which drugs exert their actions is an important challenge in advancing the use of high-dimensional biological data like phenomics. |
| | We are excited to release the first dataset of this scale probing concentration-response along with a benchmark and model to enable the research community to |
| | rapidly advance this space. |
| |
|
| | Paper published at LMRL Workshop at ICLR 2025 [RxRx3-core: Benchmarking drug-target interactions in High-Content Microscopy](https://arxiv.org/abs/2503.20158). |
| | Benchmarking code for this dataset is provided in the [EFAAR benchmarking repo](https://github.com/recursionpharma/EFAAR_benchmarking/tree/trunk/RxRx3-core_benchmarks) and [Polaris](https://polarishub.io/benchmarks/recursion/rxrx-compound-gene-activity-benchmark). |
| |
|
| | --- |
| | Loading the RxRx3-core image dataset |
| | ``` |
| | from datasets import load_dataset |
| | rxrx3_core = load_dataset("recursionpharma/rxrx3-core") |
| | ``` |
| | Loading OpenPhenom embeddings and metadata for RxRx3-core |
| | ``` |
| | from huggingface_hub import hf_hub_download |
| | import pandas as pd |
| | |
| | file_path_metadata = hf_hub_download("recursionpharma/rxrx3-core", filename="metadata_rxrx3_core.csv",repo_type="dataset") |
| | file_path_embs = hf_hub_download("recursionpharma/rxrx3-core", filename="OpenPhenom_rxrx3_core_embeddings.parquet",repo_type="dataset") |
| | |
| | open_phenom_embeddings = pd.read_parquet(file_path_embs) |
| | rxrx3_core_metadata = pd.read_csv(file_path_metadata) |
| | ``` |
| |
|
