ManiFasta is presented, a tool enabling users to generate standardized, reproducible, and robustly documented protein reference sets from diverse input sources and datatypes, and the value of maniFasta is highlighted in the context of salivary metaproteomics, addressing the need for a taxonomically comprehensive reference database.
Over the past few years, the increasing interest in analyzing the proteome of extinct and nonmodel organisms has generated a new field of research expanding the scope of proteomics. The lack of curated databases and/or molecular data from these organisms forces researchers to manually search in different public repositories for related protein sequences, either for MS/MS peptide identification or ZooMS marker annotation. This can lead to format incongruences and hinder reproducibility between studies. To address this issue, we introduce ProteoParc, a user-friendly software that builds reference databases by systematically downloading and processing protein sequences from the most widely used public repositories. The pipeline's output is a nonredundant protein database, formatted in a way to be interpreted by typical peptide identification software. Moreover, the user can adjust the database dimension and composition by applying different criteria to include only a certain number of genes or species. Thus, ProteoParc is an easy and fast, custom-made bioinformatic tool useful for future paleoproteomics analysis in ancient samples related to understudied organisms.
Guillermo Carrillo-Martin, Johanna Krueger, T. Marquès-Bonet et al.· Journal of Proteome Research· 0 citations
Reproducibility challenges scientific reporting, including metagenomics, where increasingly complex bioinformatics pipelines hinder transparency, comparability, and customization for life science students globally. To address this demanding task, we built an open, interactive and web-based tutorial that guides scholars with basic command-line skills through the detailed development of a validated and reproducible Nextflow metagenomics classification pipeline. As important features, the tutorial emphasizes simplicity, modularity, and containerization, which empowers users with both conceptual understanding and practical implementation skills. Noteworthy, this tutorial provides all the required files, databases, dependencies, software and environment for users to run it without the need of local installation or computational adaptations elsewhere. Finally, by offering a fully reproducible pipeline with a step-by-step developing tutorial, this work aims to lower technical barriers in microbiome bioinformatics and promote best practices in metagenomics data analysis. TaxoFlow is freely available at https://taxoflow.work/.
FEDKEA, an enzyme annotation tool leveraging protein language models, and a user-friendly, FEDKEA-based metagenomic pipeline, MEnzMap, which encompasses the entire analysis workflow—from raw data quality control to function prediction and downstream analyses are designed.
Lei Zheng, Bowen Li, Siqi Xu et al.· Science Advances· 0 citations
Reference databases shape the taxonomic resolution, uncertainty, and reproducibility of metabarcoding analyses. For ITS barcodes, public references are distributed across repositories with different taxonomic conventions, geographic coverage, and annotation practices, creating conflicts, missing ranks, and misannotations when databases are merged or compared. We introduce CurateMake, a reproducible Snakemake workflow for ITS reference database construction, harmonisation, and validation. It integrates four public sources (UNITE, BOLD, PLANiTS, and CALeDNA) and user-supplied databases, combines Catalogue of Life name harmonisation with ITSx-based region standardisation, MSA/HMM-based alignment grouping, and SATIVA phylogenetic validation. Raw, CoL-harmonised, and SATIVA-validated annotation layers are retained throughout to compare curation effects while preserving flagged records for review. We evaluated CurateMake on 3.58 million ingested sequences and controlled error-injection simulations. ITSx expanded the final harmonised database to 5.19 million barcode-resolved entries by recovering ITS1 and ITS2 sub-regions from full-length ITS records. Across the full dataset, normalised intra-cluster entropy decreased from Raw to CoL-harmonised to SATIVA-validated annotations, consistent with improved taxonomic coherence. In simulations, CurateMake achieved the highest correction rate across 1%–50% corruption and, at 15% corruption, corrected 42% ± 1% of introduced errors, compared with 28% ± 1% for CoL alone and 0% for SATIVA without the workflow’s alignment infrastructure. These results show that nomenclatural harmonisation and phylogeny-informed validation address complementary error classes, with phylogenetic validation contributing measurably only within taxon-coherent alignments in this benchmark. CurateMake therefore provides a reproducible, provenance-tracked framework for auditable ITS reference database curation in metabarcoding workflows.
Auguste Gardette, Eugeni Belda, Edi Prifti et al.· bioRxiv· 0 citations
FAIRyMAGs provides an accessible, extensible, and reproducible framework for genome-resolved metagenomics, reducing technical barriers and enabling methodological innovation through community-driven development within the adaptable Galaxy ecosystem.
P. Zierep, Mina Hojat Ansari, Patrick Bühler et al.· bioRxiv· 0 citations
Current metabarcoding pipelines are inflexible with respect to study design and are poorly suited to long-read sequence data. To address these limitations, we developed MAP, the Metabarcoding Analysis Pipeline, which is a sequence-to-answer workflow supporting the analysis of amplicons from highly multiplexed and replicated study designs. Although MAP can analyze amplicons of any length from any genetic marker, it includes several features tailored to long-read COI metabarcoding. MAP installs from a Docker container and requires only sequence data, a parameters file, and a reference library. It produces intuitive reports, enabling users to evaluate their data immediately after analysis. We validate MAP by showing that it generates biodiversity estimates that correspond closely to a ground-truth dataset of single-specimen DNA barcode data and by demonstrating that it outperforms alternative platforms for COI metabarcoding. MAP is free, open-source, and available from: https://github.com/cbg-innov/MAP.
S. W. Prosser, Nicholas W. Bard, Ken A. Thompson et al.· bioRxiv· 0 citations
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