Evidence map›Paper›PMID 37596696›Full record

ArticleMicrobiome2023

BinaRena: a dedicated interactive platform for human-guided exploration and binning of metagenomes.

Michael J Pavia, Abhinav Chede, Zijun Wu, Hinsby Cadillo-Quiroz, Qiyun Zhu

Open access · goldAbstract readVideo-Audio Media
In one paragraph

Article in Microbiome, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
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

4 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Visualizing metagenomic and metatranscriptomic data: A comprehensive review.Computational and structural biotechnology journal · 2024
    Review
  3. Article
  4. Article
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

5 authors at 2 institutions in 1 country.

Michael J PaviaSchool of Life Sciences, Arizona State University, Tempe, AZ, USA.
Abhinav ChedeBiodesign Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, AZ, USA.
Zijun WuBiodesign Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, AZ, USA.
Hinsby Cadillo-QuirozSchool of Life Sciences, Arizona State University, Tempe, AZ, USA. hinsby@asu.edu.
Qiyun ZhuSchool of Life Sciences, Arizona State University, Tempe, AZ, USA. qiyun.zhu@asu.edu.
Arizona State University · USUniversity of Illinois Urbana-Champaign · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundExploring metagenomic contigs and "binning" them into metagenome-assembled genomes (MAGs) are essential for the delineation of functional and evolutionary guilds within microbial communities. Despite the advances in automated binning algorithms, their capabilities in recovering MAGs with accuracy and biological relevance are so far limited. Researchers often find that human involvement is necessary to achieve representative binning results. This manual process however is expertise demanding and labor intensive, and it deserves to be supported by software infrastructure.

resultsWe present BinaRena, a comprehensive and versatile graphic interface dedicated to aiding human operators to explore metagenome assemblies via customizable visualization and to associate contigs with bins. Contigs are rendered as an interactive scatter plot based on various data types, including sequence metrics, coverage profiles, taxonomic assignments, and functional annotations. Various contig-level operations are permitted, such as selection, masking, highlighting, focusing, and searching. Binning plans can be conveniently edited, inspected, and compared visually or using metrics including silhouette coefficient and adjusted Rand index. Completeness and contamination of user-selected contigs can be calculated in real time. In demonstration of BinaRena's usability, we show that it facilitated biological pattern discovery, hypothesis generation, and bin refinement in a complex tropical peatland metagenome. It enabled isolation of pathogenic genomes within closely related populations from the gut microbiota of diarrheal human subjects. It significantly improved overall binning quality after curating results of automated binners using a simulated marine dataset.

conclusionsBinaRena is an installation-free, dependency-free, client-end web application that operates directly in any modern web browser, facilitating ease of deployment and accessibility for researchers of all skill levels. The program is hosted at https://github.com/qiyunlab/binarena , together with documentation, tutorials, example data, and a live demo. It effectively supports human researchers in intuitive interpretation and fine tuning of metagenomic data. Video Abstract.

Indexed as

MetagenomeMicrobiotaAlgorithmsBiological EvolutionDiarrheaHumansBinningContigsHuman factorInteractiveJavaScriptMetagenomicsVisualization

Identifiers

PMID37596696
PMCPMC10439608
OpenAlexW4385997331

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.