Evidence map›Paper›PMID 41278006›Full record

ArticleBioinformatics advances2025

BEREN: a bioinformatic tool for recovering giant viruses, polinton-like viruses, and virophages in metagenomic data.

Benjamin Minch, Mohammad Moniruzzaman

Abstract read
In one paragraph

Article in Bioinformatics advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Benjamin MinchDepartment of Marine Biology and Ecology, Rosenstiel School of Marine, Atmospheric, and Earth Science, University of Miami, Miami, FL 33149, United States.
Mohammad MoniruzzamanDepartment of Marine Biology and Ecology, Rosenstiel School of Marine, Atmospheric, and Earth Science, University of Miami, Miami, FL 33149, United States.ORCID https://orcid.org/0000-0001-9337-3874

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motivation: Viruses in the kingdom Bamfordvirae, specifically giant viruses (NCLDVs) in the phylum Nucleocytoviricota and smaller members in the Preplasmiviricota phylum, are widespread and important groups of viruses that infect eukaryotes. While viruses in this kingdom, such as giant viruses, polinton-like viruses, and virophages, have gained large interest from researchers in recent years, there is still a lack of streamlined tools for the recovery of their genomes from metagenomic datasets. Results: Here, we present, BEREN, a comprehensive bioinformatic tool to unlock the diversity of these viruses in metagenomes through five modules for NCLDV genome, contig, and marker gene recovery, metabolic protein annotation, and Preplasmiviricota genome identification and annotation. BEREN's performance was benchmarked against other mainstream virus recovery tools using a mock metagenome, demonstrating superior recovery rates of NCLDV contigs and Preplasmiviricota genomes. Overall, BEREN offers a user-friendly, transparent bioinformatic solution for studying the ecological and functional roles of these eukaryotic viruses, facilitating broader access to their metagenomic analysis. Availability and implementation: BEREN is available at https://gitlab.com/benminch1/BEREN, and results from testing BEREN on a real-world metagenome are available in the Supplementary Files.

Identifiers

PMID41278006
PMCPMC12638062

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Registered trials

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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.