GWASStudio: A Tool for Genomic Data Management

alt text

Overview

GWASStudio is a powerful CLI tool designed for efficient storage, retrieval, and querying of genomic summary statistics. It offers a high-performance infrastructure for handling and analyzing large-scale GWAS and QTL datasets, enabling seamless cross-dataset exploration.

Please see the documentation at https://ht-diva.github.io/gwasstudio/

Core Purpose

GWASStudio provides a unified interface across the CDH infrastructure, handling the ingestion, storage, querying and export of genomic data using high-performance technologies.

Key Functionalities

GWASStudio consists of several key functionalities:

1. Data Ingestion

Data Ingestion: Imports summary statistics data and its metadata associated.
Support for Multiple Storage Options: Works with both local filesystems and cloud storage (S3).

2. Data Querying

Flexible Search: Enables searching metadata using template files.

3. Data Export

Selective Export: Extracts subsets of data and its metadata associated based on genomic regions, SNPs, or the entire set of data.

Technical Architecture

GWASStudio leverages several advanced technologies:

TileDB Embedded: A high-performance array storage engine that enables efficient storage and retrieval of genomic data.
MongoDB: A flexible, scalable NoSQL database used for storing and querying metadata associated with genomic datasets.
Dask: Provides distributed computing capabilities for processing large datasets.
Python Ecosystem: Built on Python with libraries like Click/Cloup for CLI interfaces, Pandas for data manipulation, and various genomics-specific tools.

Installation

For detailed installation instructions, please refer to the documentation at https://ht-diva.github.io/gwasstudio/

Usage

For detailed instructions on how to use this tool, please refer to the documentation and check the cli_test scripts for a practical guide by examples.

Citation

Example files are derived from:

The variant call format provides efficient and robust storage of GWAS summary statistics. Matthew Lyon, Shea J Andrews, Ben Elsworth, Tom R Gaunt, Gibran Hemani, Edoardo Marcora. bioRxiv 2020.05.29.115824; doi: https://doi.org/10.1101/2020.05.29.115824

Metadata

Release files for gwasstudio 3.3.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for gwasstudio 3.3.1
File	Size	Uploaded
gwasstudio-3.3.1.tar.gz	61.3 kB	Sep 15, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for gwasstudio 3.3.1
File	Interpreter	ABI	Platform	Reset
gwasstudio-3.3.1-py3-none-any.whl 76.3 kB Sep 15, 2026	Python 3	none	any	Details

Total release size: 137.6 kB

Release files / gwasstudio-3.3.1.tar.gz

Download URL	gwasstudio-3.3.1.tar.gz
Size	61.3 kB
Tags	Source
SHA-256 checksum How to use checksums	`168eac44a535ee1c39e1348c00b2975489dd4871fe4b4c0d35a7c13bc00adfb0`
BLAKE2b-256 checksum How to use checksums	`12eb6e123dc82f42df7ec02836aaafe07db103319f3637d02d64996e1fa3471b`
Upload date	Sep 15, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/ht-diva/gwasstudio
Publishing commit: github.com/ht-diva/gwasstudio/tree/308048e9696e7ee077bdd9f7b8d042e8d9788b0d

Workflow

Publishing configuration: github.com/ht-diva/gwasstudio/blob/308048e9696e7ee077bdd9f7b8d042e8d9788b0d/.github/workflows/release.yml
Publishing logs: github.com/ht-diva/gwasstudio/actions/runs/34976977933/attempts/1

Artifact

Subject: gwasstudio-3.3.1.tar.gz
SHA-256 checksum: 168eac44a535ee1c39e1348c00b2975489dd4871fe4b4c0d35a7c13bc00adfb0 Verifying attestations

Release files / gwasstudio-3.3.1-py3-none-any.whl

Download URL	gwasstudio-3.3.1-py3-none-any.whl
Size	76.3 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`1d43eade48f313735f9318b57e83dbcc2d77f46bb827b7884e33fd35936c2084`
BLAKE2b-256 checksum How to use checksums	`ca47d56e1740abfb8c3b34d1b2ca28b91c57118b834feeed763efa756ce37d5d`
Upload date	Sep 15, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/ht-diva/gwasstudio
Publishing commit: github.com/ht-diva/gwasstudio/tree/308048e9696e7ee077bdd9f7b8d042e8d9788b0d

Workflow

Publishing configuration: github.com/ht-diva/gwasstudio/blob/308048e9696e7ee077bdd9f7b8d042e8d9788b0d/.github/workflows/release.yml
Publishing logs: github.com/ht-diva/gwasstudio/actions/runs/34976977933/attempts/1

Artifact

Subject: gwasstudio-3.3.1-py3-none-any.whl
SHA-256 checksum: 1d43eade48f313735f9318b57e83dbcc2d77f46bb827b7884e33fd35936c2084 Verifying attestations