q2-fondue

q2-fondue: Nucleotide Sequence Metadata Acquisition and Provenance Tracking

q2-fondue provides programmatic acquisition, management, and meta-analysis support for nucleotide sequence metadata by enabling reproducible retrieval of datasets from the NCBI Sequence Read Archive (SRA) with integrated provenance tracking.


Key Features:

  • Provenance Tracking: Records complete data lineage from SRA download through downstream processing to ensure reproducibility and transparency.
  • QIIME 2 Integration: Operates within the QIIME 2 ecosystem to manage amplicon, whole genome, and metagenome datasets for microbiome analysis.
  • Data Integrity Management: Prevents data loss due to storage space exhaustion during large-scale genomic data acquisition and processing.
  • Publication-Linked Retrieval: Downloads sequence (meta)data associated with specific scientific publications to support structured meta-analyses.

Scientific Applications:

  • Meta-analysis of Public Sequence Data: Enables reproducible reuse and integration of amplicon, whole genome, and metagenome datasets in genomics, microbiology, and bioinformatics research.

Methodology:

Implements programmatic access to the NCBI Sequence Read Archive (SRA) for automated dataset retrieval and metadata management, with full provenance capture integrated into QIIME 2 workflows to support transparent and reproducible sequence-based analyses.

Topics

Details

License:
BSD-3-Clause
Cost:
Free of charge
Tool Type:
command-line tool
Operating Systems:
Mac, Linux, Windows
Programming Languages:
Python
Added:
11/26/2022
Last Updated:
11/26/2022

Operations

Data Inputs & Outputs

Data retrieval

Publications

Ziemski M, Adamov A, Kim L, Flörl L, Bokulich NA. Reproducible acquisition, management and meta-analysis of nucleotide sequence (meta)data using q2-fondue. Bioinformatics. 2022;38(22):5081-5091. doi:10.1093/bioinformatics/btac639. PMID:36130056. PMCID:PMC9665871.

PMID: 36130056
PMCID: PMC9665871
Funding: - Strategic Focus Area ‘Personalized Health and Related Technologies: #2021-362 - Swiss National Science Foundation: 310030_204275

Documentation