The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 299, in get_dataset_config_info
for split_generator in builder._split_generators(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 125, in _split_generators
analyze(archives, downloaded_dirs, split_name)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 79, in analyze
if os.path.isfile(downloaded_files_or_dirs[0]):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/streaming.py", line 75, in wrapper
return function(*args, download_config=download_config, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 747, in xisfile
fs, *_ = url_to_fs(path, **storage_options)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 395, in url_to_fs
fs = filesystem(protocol, **inkwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/registry.py", line 293, in filesystem
return cls(**storage_options)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 80, in __call__
obj = super().__call__(*args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/zip.py", line 62, in __init__
self.zip = zipfile.ZipFile(
File "/usr/local/lib/python3.9/zipfile.py", line 1266, in __init__
self._RealGetContents()
File "/usr/local/lib/python3.9/zipfile.py", line 1333, in _RealGetContents
raise BadZipFile("File is not a zip file")
zipfile.BadZipFile: File is not a zip file
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 353, in get_dataset_split_names
info = get_dataset_config_info(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 304, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Pan-Multiplex (Pan-M) dataset
This dataset was constructed to train the Nimbus model for the publication "Automated classification of cellular expression in multiplexed imaging data with Nimbus".
The dataset contains multiplexed images from different modalities, tissues and protein marker panels. It was constructed by a semi-automatic pipeline, where the cell types assigned by the authors of the original studies that published the data, where mapped back to their expected marker activity. In addition, for 3 FoVs of each dataset, 4 expert annotators proofread ~1.1M annotations which served as the gold-standard for assesing the algorithm.
More details to the construction of the dataset can be found in the paper. The dataset consists of five subsets named codex_colon,mibi_breast,mibi_decidua,vectra_colon,vectra_pancreas, each in an individual folder.
After unzipping, the data should be stored in the following folder structure to use the code provided for training and inference. To construct the binary segmentation maps used for training, you can use the code in segmentation_data_prep.py and simple_data_prep.py in the training repository.
.
├── data
│ ├── codex_colon
│ ├── vectra_colon
│ ├── vectra_pancreas
│ ├── mibi_decidua
│ ├── mibi_breast
│ ├── experimental_results.csv
│ ├── gt_pred_ie_consolidated.csv
The MIBI Breast dataset is currently not available. The original study where this dataset comes from is still under review. Once the study is published, the dataset will be available here.
When using the dataset please cite
@article{rum2024nimbus,
title={Automated classification of cellular expression in multiplexed imaging data with Nimbus},
author={Rumberger, J. Lorenz and Greenwald, Noah F. and Ranek, Jolene S. and Boonrat, Potchara and Walker, Cameron and Franzen, Jannik and Varra, Sricharan Reddy and Kong, Alex and Sowers, Cameron and Liu, Candace C. and Averbukh, Inna and Piyadasa, Hadeesha and Vanguri, Rami and Nederlof, Iris and Wang, Xuefei Julie and Van Valen, David and Kok, Marleen and Hollman, Travis J. and Kainmueller, Dagmar and Angelo, Michael},
journal={bioRxiv},
pages={2024--05},
year={2024},
publisher={Cold Spring Harbor Laboratory}
}
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