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Updated: Aug 28, 2025

G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome
Published on: March 22, 2018
Reproducible acquisition, management and meta-analysis of nucleotide sequence (meta)data using q2-fondue
Michal Ziemski1, Anja Adamov1, Lina Kim1
1Laboratory of Food Systems Biotechnology, Institute of Food, Nutrition, and Health, ETH Zürich, Zürich 8092, Switzerland.
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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