Open-Access Computational Biology Datasets
Project description
bedrock-bio
Open-Access Computational Biology Datasets
Description
Efficiently access a curated library of open-access computational biology datasets. Datasets support predicate pushdown and projection to the cloud storage backend, enabling quick, iterative access to otherwise massive, unwieldy datasets.
bedrock_bio consists of three user-facing functions:
list_datasets(): returns a list of available dataset identifiersdescribe_dataset('<name>'): returns metadata, citation, and column definitions for a datasetload_dataset('<name>', **filters): takes a dataset name and required partition filters, and returns a lazy DuckDB relation
DuckDB methods (filter, select, limit) can be used on the relation
returned by load_dataset to push down additional row filters and column
selections to the storage backend.
Installation
To install the latest release from PyPI:
pip install bedrock-bio
Or install the current development version from GitHub:
pip install git+https://github.com/bedrock-bio/bedrock-bio-client.git@main#subdirectory=python
Examples
import bedrock_bio as bb
List available datasets:
bb.list_datasets()
Describe a dataset to see its metadata, citation, and columns:
bb.describe_dataset('ukb_ppp.pqtls')
Lazily load a dataset with required partition filters, select columns, and collect into an in-memory data frame:
df = bb.load_dataset('ukb_ppp.pqtls', ancestry='EUR', protein_id='A0FGR8', panel='Inflammation') \
.select('chromosome, position, effect_allele, other_allele, beta, neg_log_10_p_value') \
.fetchdf()
Dataset Requests
To request the addition of a new dataset to the library, open an issue.
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