Reproducible Acquisition, Management and Meta-analysis of Nucleotide Sequence (meta)data Using Q2-fondue

Overview

Journal Bioinformatics

Publisher Oxford University Press

Specialty Biology

Date 2022 Sep 21

PMID 36130056

Authors

Michal Ziemski

Anja Adamov

Lina Kim

Lena Florl

Nicholas A Bokulich

Affiliations

Soon will be listed here.

Abstract

Motivation: The volume of public nucleotide sequence data has blossomed over the past two decades and is ripe for re- and meta-analyses to enable novel discoveries. However, reproducible re-use and management of sequence datasets and associated metadata remain critical challenges. We created the open source Python package q2-fondue to enable user-friendly acquisition, re-use and management of public sequence (meta)data while adhering to open data principles.

Results: q2-fondue allows fully provenance-tracked programmatic access to and management of data from the NCBI Sequence Read Archive (SRA). Unlike other packages allowing download of sequence data from the SRA, q2-fondue enables full data provenance tracking from data download to final visualization, integrates with the QIIME 2 ecosystem, prevents data loss upon space exhaustion and allows download of (meta)data given a publication library. To highlight its manifold capabilities, we present executable demonstrations using publicly available amplicon, whole genome and metagenome datasets.

Availability And Implementation: q2-fondue is available as an open-source BSD-3-licensed Python package at https://github.com/bokulich-lab/q2-fondue. Usage tutorials are available in the same repository. All Jupyter notebooks used in this article are available under https://github.com/bokulich-lab/q2-fondue-examples.

Supplementary Information: Supplementary data are available at Bioinformatics online.

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