bedrock_bio 1.3.1

Efficiently access the 'Bedrock Bio' library of open-access computational biology datasets.

bedrock-bio

Open-Access Computational Biology Datasets

Description

Efficiently access a curated library of open-access computational biology datasets. Tables support predicate pushdown and projection to the cloud storage backend, enabling quick, iterative access to otherwise massive, unwieldy tables.

bedrock_bio consists of three user-facing functions:

• list_tables(): returns a list of available table identifiers
• describe_table('<name>'): returns metadata, citation, and column definitions for a table
• load_table('<name>', **filters): takes a table name and optional partition filters, and returns a lazy DuckDB relation

DuckDB methods (filter, select, limit) can be used on the relation returned by load_table 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 tables:

bb.list_tables()

Describe a table to see its metadata, citation, and columns:

bb.describe_table('ukb_ppp.pqtls')

Lazily load a table (optionally with partition filters for partitioned tables), select columns, and collect into an in-memory data frame:

df = bb.load_table('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 table to the library, open an issue.