metaIVP: an integrative metavirome focused metagenomic processing pipeline
Metagenomic studies increasingly rely on complex, multi-tool pipelines to recover and characterize viral and non-viral genomes from mixed microbial communities. While these pipelines enable high-resolution genome recovery, limited functionality in downstream post-processing workflows and insufficient logging structures often hinder reproducibility, error tracing, and selective re-analysis. These challenges are particularly critical in metaviral analyses, where viral and non-viral genomes must be processed using distinct methodologies. To address these limitations, we introduce metaIVP, a modular, integrative, and flexible framework designed to systematically manage genome content purification, re-binning, quality assessment, and downstream analyses of viral and non-viral metagenomic contexts. The metaIVP framework is organized into hierarchical modules, each governed by dedicated log files that explicitly control execution state and re-runnability. Contig-level and bin-level analytical and purification steps are implemented as essential modules to isolate genome contents, followed by separate viral and non-viral post-processing workflows. Viral workflows incorporate contamination detection, genome quality evaluation, host prediction, and virus-specific binning. Non-viral analyses include genome binning, alignment and mapping statistics, genome quality assessment, and replication rate estimation. Checkpoints are explicitly defined such that deletion of selected module- or sub-module-level logs enables targeted re-execution of specific analytical steps without rerunning the full pipeline. All analyses are integrated to depict a comprehensive system in the metagenomic samples, with focus on the metaviromic information. The usage of metaIVP was demonstrated using both a well-controlled human gut virome dataset and a geographically structured environmental metavirome dataset, showing its broad applicability across host-associated and environmental systems. The pipeline effectively separates viral and non-viral genomic content, improves viral bin purity, and preserves sample-specific functional, taxonomic, and host-association features after virome enrichment. Compared with recent state-of-the-art approaches, metaIVP achieves comparable performance, particularly when optional re-binning with vRhyme is applied, while maintaining a higher fraction of high-confidence viral bins. The metaIVP addresses a key gap in metavirome analysis by jointly characterizing viral and non-viral genomic components and supporting integrative downstream analyses within a single framework. Its user-friendly, modular, and controllable design allows flexible execution and provides a foundation for incorporating additional downstream analytical tools as metavirome methodologies continue to evolve.