Evidence map›Paper›PMID 33691615›Full record

ArticleBMC bioinformatics2021

AgroSeek: a system for computational analysis of environmental metagenomic data and associated metadata.

Xiao Liang, Kyle Akers, Ishi Keenum, Lauren Wind, Suraj Gupta, Chaoqi Chen, Reem Aldaihani, Amy Pruden, Liqing Zhang, Katharine F Knowlton and 2 more

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 36% 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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. 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

12 authors at 2 institutions in 2 countries.

Xiao LiangDepartment of Computer Science, Virginia Polytechnic Institute and State University, 24061, Blacksburg, USA. xliangvt@vt.edu.ORCID http://orcid.org/0000-0001-8789-6732
Kyle AkersInterdisciplinary PhD Program in Genetics, Bioinformatics, and Computational Biology, Virginia Polytechnic Institute and State University, 24061, Blacksburg, USA.
Ishi KeenumDepartment of Civil and Environmental Engineering, Virginia Polytechnic Institute and State University, 24061, Blacksburg, USA.
Lauren WindDepartment of Biological Systems Engineering, Virginia Polytechnic Institute and State University, 24061, Blacksburg, USA.
Suraj GuptaInterdisciplinary PhD Program in Genetics, Bioinformatics, and Computational Biology, Virginia Polytechnic Institute and State University, 24061, Blacksburg, USA.
Chaoqi ChenSchool of Resource and Environmental Science, Wuhan University, 430072, Wuhan, China.
Reem AldaihaniDepartment of Computer Science, Virginia Polytechnic Institute and State University, 24061, Blacksburg, USA.
Amy PrudenDepartment of Civil and Environmental Engineering, Virginia Polytechnic Institute and State University, 24061, Blacksburg, USA.
Liqing ZhangDepartment of Computer Science, Virginia Polytechnic Institute and State University, 24061, Blacksburg, USA.
Katharine F KnowltonDepartment of Dairy Science, Virginia Polytechnic Institute and State University, 24061, Blacksburg, USA.
Kang XiaSchool of Plant and Environmental Science, Virginia Polytechnic Institute and State University, 24061, Blacksburg, USA.
Lenwood S HeathDepartment of Computer Science, Virginia Polytechnic Institute and State University, 24061, Blacksburg, USA.
Virginia Tech · USWuhan University · CN

Funding

National Institute of Food and Agriculture 2015-68003-23050National Institute of Food and Agriculture 2017-68003-26498U.S. National Science Foundation Partnership in International Research and Education 1545756
6 · The paper itself

Abstract

backgroundMetagenomics is gaining attention as a powerful tool for identifying how agricultural management practices influence human and animal health, especially in terms of potential to contribute to the spread of antibiotic resistance. However, the ability to compare the distribution and prevalence of antibiotic resistance genes (ARGs) across multiple studies and environments is currently impossible without a complete re-analysis of published datasets. This challenge must be addressed for metagenomics to realize its potential for helping guide effective policy and practice measures relevant to agricultural ecosystems, for example, identifying critical control points for mitigating the spread of antibiotic resistance.

resultsHere we introduce AgroSeek, a centralized web-based system that provides computational tools for analysis and comparison of metagenomic data sets tailored specifically to researchers and other users in the agricultural sector interested in tracking and mitigating the spread of ARGs. AgroSeek draws from rich, user-provided metagenomic data and metadata to facilitate analysis, comparison, and prediction in a user-friendly fashion. Further, AgroSeek draws from publicly-contributed data sets to provide a point of comparison and context for data analysis. To incorporate metadata into our analysis and comparison procedures, we provide flexible metadata templates, including user-customized metadata attributes to facilitate data sharing, while maintaining the metadata in a comparable fashion for the broader user community and to support large-scale comparative and predictive analysis.

conclusionAgroSeek provides an easy-to-use tool for environmental metagenomic analysis and comparison, based on both gene annotations and associated metadata, with this initial demonstration focusing on control of antibiotic resistance in agricultural ecosystems. Agroseek creates a space for metagenomic data sharing and collaboration to assist policy makers, stakeholders, and the public in decision-making. AgroSeek is publicly-available at https://agroseek.cs.vt.edu/ .

Indexed as

Environmental MicrobiologyGenes, BacterialMetadataMetagenomicsDrug Resistance, MicrobialEcosystemInternetMetagenomeSoftwareAntibiotic resistanceData scienceMetadataMetagenomicsWeb server

Identifiers

PMID33691615
PMCPMC7944603
OpenAlexW3134196097

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.