Evidence map›Paper›PMID 35620097›Full record

ArticleFrontiers in microbiology2022

Comparative Analysis of Metagenomics and Metataxonomics for the Characterization of Vermicompost Microbiomes.

Marcos Pérez-Losada, Dhatri Badri Narayanan, Allison R Kolbe, Ignacio Ramos-Tapia, Eduardo Castro-Nallar, Keith A Crandall, Jorge Domínguez

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.6field-weighted citation impact, top 11% 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

6 citing papers in PubMed, 21 citations in OpenAlex.

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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

7 authors at 4 institutions in 4 countries.

Marcos Pérez-LosadaComputational Biology Institute, The George Washington University, Washington, DC, United States.
Dhatri Badri NarayananComputational Biology Institute, The George Washington University, Washington, DC, United States.
Allison R KolbeComputational Biology Institute, The George Washington University, Washington, DC, United States.
Ignacio Ramos-TapiaInstituto de Investigación Interdisciplinaria (I3), Universidad de Talca, Talca, Chile.
Eduardo Castro-NallarCIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Vairão, Portugal.
Keith A CrandallComputational Biology Institute, The George Washington University, Washington, DC, United States.
Jorge DomínguezGrupo de Ecoloxía Animal (GEA), Universidade de Vigo, Vigo, Spain.
George Washington University · USUniversity of Talca · CLMilken Institute · USUniversidade de Vigo · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The study of microbial communities or microbiotas in animals and environments is important because of their impact in a broad range of industrial applications, diseases and ecological roles. High throughput sequencing (HTS) is the best strategy to characterize microbial composition and function. Microbial profiles can be obtained either by shotgun sequencing of genomes, or through amplicon sequencing of target genes (e.g., 16S rRNA for bacteria and ITS for fungi). Here, we compared both HTS approaches at assessing taxonomic and functional diversity of bacterial and fungal communities during vermicomposting of white grape marc. We applied specific HTS workflows to the same 12 microcosms, with and without earthworms, sampled at two distinct phases of the vermicomposting process occurring at 21 and 63 days. Metataxonomic profiles were inferred in DADA2, with bacterial metabolic pathways predicted

Indexed as

16S rRNAearthwormgrape marcITSmetagenomicsmetataxonomicsmicrobiomevermicompost

Identifiers

PMID35620097
PMCPMC9127802
OpenAlexW4229458236

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.