Biology subjects

Ziemski, M.

Publications and source records attributed to Ziemski, M..

3 recordsLinked to original sources

bioRxiv2025

MOSHPIT: accessible, reproducible metagenome data science on the QIIME 2 framework

Metagenome sequencing has revolutionized functional microbiome analysis across diverse ecosystems, but is fraught with technical hurdles. We introduce MOSHPIT (https://moshpit.readthedocs.io), software built on the QIIME 2 framework (Q2F) that integrates best-in-class CAMI2-validated metagenome tools with robust provenance tracking and multiple user interfaces, enabling streamlined, reproducible metagenome analysis for all expertise levels. By building on Q2F, MOSHPIT enhances scalability, interoperability, and reproducibility in complex workflows, democratizing and accelerating discovery at the frontiers of metagenomics.

bioinformatics↗

bioRxiv2022

Reproducible acquisition, management, and meta-analysis of nucleotide sequence (meta)data using q2-fondue

The volume of public nucleotide sequence data has blossomed over the past two decades, enabling novel discoveries via re-analysis, meta-analyses, and comparative studies for uncovering general biological trends. However, reproducible re-use and management of sequence datasets remains a challenge. We created the software plugin q2-fondue to enable user-friendly acquisition, re-use, and management of public nucleotide sequence (meta)data while adhering to open data principles. The software allows fully provenance-tracked programmatic access to and management of data from the Sequence Read Archive (SRA). Sequence data and accompanying metadata retrieved with q2-fondue follow a validated format, which is interoperable with the QIIME 2 ecosystem and its multiple user interfaces. To highlight the manifold capabilities of q2-fondue, we present several demonstration analyses using amplicon, whole genome, and shotgun metagenome datasets. These use cases demonstrate how q2-fondue increases analysis reproducibility and transparency from data download to final visualizations by including source details in the integrated provenance graph. We believe q2-fondue will lower existing barriers to comparative analyses of nucleotide sequence data, enabling more transparent, open, and reproducible conduct of meta-analyses. q2-fondue is a Python 3 package released under the BSD 3-clause license at https://github.com/bokulich-lab/q2-fondue.

bioinformatics↗

bioRxiv2020

RESCRIPt: Reproducible sequence taxonomy reference database management for the masses

BackgroundNucleotide sequence and taxonomy reference databases are critical resources for widespread applications including marker-gene and metagenome sequencing for microbiome analysis, diet metabarcoding, and environmental DNA (eDNA) surveys. Reproducibly generating, managing, using, and evaluating nucleotide sequence and taxonomy reference databases creates a significant bottleneck for researchers aiming to generate custom sequence databases. Furthermore, database composition drastically influences results, and lack of standardizations limits cross-study comparisons. To address these challenges, we developed RESCRIPt, a software package for reproducible generation and management of reference sequence taxonomy databases, including dedicated functions that streamline creating databases from popular sources, and functions for evaluating, comparing, and interactively exploring qualitative and quantitative characteristics across reference databases. ResultsTo highlight the breadth and capabilities of RESCRIPt, we provide several examples for working with popular databases for microbiome profiling (SILVA, Greengenes, NCBI-RefSeq, GTDB), eDNA, and diet metabarcoding surveys (BOLD, GenBank), as well as for genome comparison. We show that bigger is not always better, and reference databases with standardized taxonomies and those that focus on type strains have quantitative advantages, though may not be appropriate for all use cases. Most databases appear to benefit from some curation (quality filtering), though sequence clustering appears detrimental to database quality. Finally, we demonstrate the breadth and extensibility of RESCRIPt for reproducible workflows with a comparison of global hepatitis genomes. ConclusionsRESCRIPt provides tools to democratize the process of reference database acquisition and management, enabling researchers to reproducibly and transparently create reference materials for diverse research applications. RESCRIPt is released under a permissive BSD-3 license at https://github.com/bokulich-lab/RESCRIPt.

bioinformatics↗