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Advancing integration of data on food microbiome studies: FoodMicrobionet 3.1, a major upgrade of the FoodMicrobionet database
- Source :
- International journal of food microbiology 305 (2019). doi:10.1016/j.ijfoodmicro.2019.108249, info:cnr-pdr/source/autori:Parente, Eugenio; De Filippis, Francesca; Danilo, Ercolini; Ricciardi, Annamaria; Zotta, Teresa/titolo:Advancing integration of data on food microbiome studies: FoodMicrobionet 3.1, a major upgrade of the FoodMicrobionet database/doi:10.1016%2Fj.ijfoodmicro.2019.108249/rivista:International journal of food microbiology/anno:2019/pagina_da:/pagina_a:/intervallo_pagine:/volume:305
- Publication Year :
- 2019
-
Abstract
- We present a new version of FoodMicrobionet, a database for the exploration of food bacterial communities. The database, available as an app built with the Shiny package of R, includes data from 44 studies and 2234 samples (food or food environment), covering dairy, meat, fruit and vegetables, cereal based and ready-to-eat foods. The interactive interface allows exploration of data, access to external resources (on line versions of the studies, sequence data on SRA, taxonomic databases), ltering samples on the basis of a number of criteria, aggregation of samples and bacterial taxa and export of data in a variety of formats. FoodMicrobionet is the largest collection of data on food bacterial communities and, due to the structure of sample metadata, largely derived from the European Food Safety Agency FoodEx2 classi cation, makes comparison and re-analysis of data from published and unpublished studies easy. Data exported from FoodMicrobionet can be readily used for graphical and sta- tistical meta-analyses using open-source software (Gephi, Cytoscape, CoNet, and R packages and apps, such as phyloseq and Shiny-Phyloseq) thus providing scientists, risk assessors and industry with a wealth of information on the structure of food biomes.
- Subjects :
- Meat
Databases, Factual
Computer science
Interface (computing)
Sample (statistics)
computer.software_genre
Microbiology
Database
03 medical and health sciences
Software
16S metagenomics
Food bacterial microbiota
Animals
030304 developmental biology
Structure (mathematical logic)
0303 health sciences
Bacteria
030306 microbiology
business.industry
Amplicon targeted high throughput sequencing
Microbiota
General Medicine
Food safety
Variety (cybernetics)
Metadata
Upgrade
Food Microbiology
16S metagenomic
business
computer
Food Science
Subjects
Details
- ISSN :
- 18793460
- Volume :
- 305
- Database :
- OpenAIRE
- Journal :
- International journal of food microbiology
- Accession number :
- edsair.doi.dedup.....5824f49d0fd3ac2af87d5281fad8e41c