Trial reportMicrobiome2019
Mining, analyzing, and integrating viral signals from metagenomic data.
Trial report in Microbiome, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
40 citing papers in PubMed, 2 syntheses or guidelines pooled it, 89 citations in OpenAlex.
- Bacteriophage-mediated gut microbiota regulation: a bibliometric landscape analysis (2005-2024).Frontiers in microbiology · 2026Pooled it
- Precision phage therapy in the AI/ML era: a systematic review of discovery-to-clinical translation evidence.Frontiers in microbiology · 2026Pooled it
- Enhanced multi-omic viral profiling from microbial community sequencing with BAQLaVa.bioRxiv : the preprint server for biology · 2026Article
- Phage quest: a beginner's guide to explore viral diversity in the prokaryotic world.Briefings in bioinformatics · 2025Review
- The Aggregated Gut Viral Catalogue (AVrC): A unified resource for exploring the viral diversity of the human gut.PLoS computational biology · 2025Article
- Article
- Characterizing the gut phageome and phage-borne antimicrobial resistance genes in pigs.Microbiome · 2024Article
- Correlation between the gut microbiome and neurodegenerative diseases: a review of metagenomics evidence.Neural regeneration research · 2024Review
- Benchmarking informatics approaches for virus discovery: caution is needed when combiningmSystems · 2024Article
- Automated classification of giant virus genomes using a random forest model built on trademark protein families.Npj viruses · 2024Article
- Hecatomb: an integrated software platform for viral metagenomics.GigaScience · 2024Article
- VIRify: An integrated detection, annotation and taxonomic classification pipeline using virus-specific protein profile hidden Markov models.PLoS computational biology · 2023Article
- Gauge your phage: benchmarking of bacteriophage identification tools in metagenomic sequencing data.Microbiome · 2023Article
- Evaluation of computational phage detection tools for metagenomic datasets.Frontiers in microbiology · 2023Article
- The human gut virome: composition, colonization, interactions, and impacts on human health.Frontiers in microbiology · 2023Review
- Temporal and regulatory dynamics of the inner ear transcriptome during development in mice.Scientific reports · 2022Article
- What the Phage: a scalable workflow for the identification and analysis of phage sequences.GigaScience · 2022Article
- Alterations of gut viral signals in atrial fibrillation: complex linkage with gut bacteriome.Aging · 2022Article
- Low Intrahost and Interhost Genetic Diversity ofViruses · 2022Article
- Computational Tools for the Analysis of Uncultivated Phage Genomes.Microbiology and molecular biology reviews : MMBR · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 6 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundViruses are important components of microbial communities modulating community structure and function; however, only a couple of tools are currently available for phage identification and analysis from metagenomic sequencing data. Here we employed the random forest algorithm to develop VirMiner, a web-based phage contig prediction tool especially sensitive for high-abundances phage contigs, trained and validated by paired metagenomic and phagenomic sequencing data from the human gut flora.
resultsVirMiner achieved 41.06% ± 17.51% sensitivity and 81.91% ± 4.04% specificity in the prediction of phage contigs. In particular, for the high-abundance phage contigs, VirMiner outperformed other tools (VirFinder and VirSorter) with much higher sensitivity (65.23% ± 16.94%) than VirFinder (34.63% ± 17.96%) and VirSorter (18.75% ± 15.23%) at almost the same specificity. Moreover, VirMiner provides the most comprehensive phage analysis pipeline which is comprised of metagenomic raw reads processing, functional annotation, phage contig identification, and phage-host relationship prediction (CRISPR-spacer recognition) and supports two-group comparison when the input (metagenomic sequence data) includes different conditions (e.g., case and control). Application of VirMiner to an independent cohort of human gut metagenomes obtained from individuals treated with antibiotics revealed that 122 KEGG orthology and 118 Pfam groups had significantly differential abundance in the pre-treatment samples compared to samples at the end of antibiotic administration, including clustered regularly interspaced short palindromic repeats (CRISPR), multidrug resistance, and protein transport. The VirMiner webserver is available at http://sbb.hku.hk/VirMiner/ .
conclusionsWe developed a comprehensive tool for phage prediction and analysis for metagenomic samples. Compared to VirSorter and VirFinder-the most widely used tools-VirMiner is able to capture more high-abundance phage contigs which could play key roles in infecting bacteria and modulating microbial community dynamics.
trial registrationThe European Union Clinical Trials Register, EudraCT Number: 2013-003378-28 . Registered on 9 April 2014.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.