Meta2Data: Automated data processing for large scale microbiome data re-analysis

Abstract

Meta2Data is a modular, largely automated pipeline implemented in Python and Bash for the retrieval, standardization, and processing of public microbiome sequencing data. It retrieves metadata from major public repositories, including INSDC and CNCB, using user-provided keywords or BioProject/BioSample identifiers. Retrieved metadata are standardized using a synonym dictionary and then subjected to manual curation. Based on the curated metadata, Meta2Data downloads the corresponding raw sequencing data and processes them using standardized workflows based on DADA2 or VSEARCH. The pipeline supports both single- and multiple-target-region datasets and produces integrated feature tables, taxonomic assignments, and phylogenetic trees for downstream microbial community analyses.

Availability and ImplementationMeta2Data is freely available at https://github.com/LinyangSun/Meta2Data and archived on Zenodo at https://doi.org/10.5281/zenodo.20670433

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BibTeX RIS

BibTeX

@misc{li2026meta2data,
  title = {{Meta2Data: Automated data processing for large scale microbiome data re-analysis}},
  author = {J. Li and A. Duplouy and L. Sun},
  howpublished = {bioRxiv},
  year = {2026},
  month = oct,
  doi = {10.64898/2026.10.01.732036},
  url = {https://www.biorxiv.org/content/10.64898/2026.10.01.732036v2},
  note = {CC BY-NC-ND},
}

RIS

TY  - UNPB
TI  - Meta2Data: Automated data processing for large scale microbiome data re-analysis
AU  - J. Li
AU  - A. Duplouy
AU  - L. Sun
PY  - 2026
DA  - 2026/10/01
PB  - bioRxiv
DO  - 10.64898/2026.10.01.732036
UR  - https://www.biorxiv.org/content/10.64898/2026.10.01.732036v2
AB  - Meta2Data is a modular, largely automated pipeline implemented in Python and Bash for the retrieval, standardization, and processing of public microbiome sequencing data. It retrieves metadata from major public repositories, including INSDC and CNCB, using user-provided keywords or BioProject/BioSample identifiers. Retrieved metadata are standardized using a synonym dictionary and then subjected to manual curation. Based on the curated metadata, Meta2Data downloads the corresponding raw sequencing data and processes them using standardized workflows based on DADA2 or VSEARCH. The pipeline supports both single- and multiple-target-region datasets and produces integrated feature tables, taxonomic assignments, and phylogenetic trees for downstream microbial community analyses.  Availability and ImplementationMeta2Data is freely available at https://github.com/LinyangSun/Meta2Data and archived on Zenodo at https://doi.org/10.5281/zenodo.20670433
ER  -

Abstract

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