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wwydmanski
/
metagenomic_curated

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The dataset viewer is not available for this dataset.
Cannot get the config names for the dataset.
Error code:   ConfigNamesError
Exception:    ImportError
Message:      To be able to use wwydmanski/metagenomic_curated, you need to install the following dependencies: pyreadr, rdata.
Please install them using 'pip install pyreadr rdata' for instance.
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
                  config_names = get_dataset_config_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1914, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1880, in dataset_module_factory
                  return HubDatasetModuleFactoryWithScript(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1504, in get_module
                  local_imports = _download_additional_modules(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 354, in _download_additional_modules
                  raise ImportError(
              ImportError: To be able to use wwydmanski/metagenomic_curated, you need to install the following dependencies: pyreadr, rdata.
              Please install them using 'pip install pyreadr rdata' for instance.

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Metagenomic curated data

This is a python repack of the curated data from the Metagenomic Data Repository.

Please refer to the study list and study metadata for the list of available datasets.

Sample usage 

ds = datasets.load_dataset("wwydmanski/metagenomic_curated", "EH1726")
X = np.array([list(i.values()) for i in ds['train']['features']])
y = np.array([x['study_condition'] for x in ds['train']['metadata']])

Finding a relevant dataset EHID

The easiest way to find an interesting study is via study metadata. After that, you can find corresponding EHIDs by referring on the https://experimenthub.bioconductor.org/title/{study_name} page.

Let's say that the ThomasAM_2018a study piqued your curiosity - it means that you will be able to find all relevant datasets on the https://experimenthub.bioconductor.org/title/ThomasAM_2018a website.

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