metagenomeFeatures: an R package for working with 16S rRNA reference databases and marker-gene survey feature data

metagenomeFeatures: an R package for working with 16S rRNA reference databases and marker-gene survey feature data

Abstract Summary We developed the metagenomeFeatures R Bioconductor package along with annotation packages for three 16S rRNA databases (Greengenes, RDP and SILVA) to facilitate working with 16S rRNA databases and marker-gene survey feature data. The metagenomeFeatures package defines two classes, M...

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Veröffentlicht in:Bioinformatics 2019-10, Vol.35 (19), p.3870-3872
Hauptverfasser: Olson, Nathan D, Shah, Nidhi, Kancherla, Jayaram, Wagner, Justin, Paulson, Joseph N, Corrada Bravo, Hector
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Applications Notes
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container_end_page 3872
container_issue 19
container_start_page 3870
container_title Bioinformatics
container_volume 35
creator Olson, Nathan D
Shah, Nidhi
Kancherla, Jayaram
Wagner, Justin
Paulson, Joseph N
Corrada Bravo, Hector
description Abstract Summary We developed the metagenomeFeatures R Bioconductor package along with annotation packages for three 16S rRNA databases (Greengenes, RDP and SILVA) to facilitate working with 16S rRNA databases and marker-gene survey feature data. The metagenomeFeatures package defines two classes, MgDb for working with 16S rRNA sequence databases, and mgFeatures for marker-gene survey feature data. The associated annotation packages provide a consistent interface to the different databases facilitating database comparison and exploration. The mgFeatures-class represents a crucial step in the development of a common data structure for working with 16S marker-gene survey data in R. Availability and implementation https://bioconductor.org/packages/release/bioc/html/metagenomeFeatures.html. Supplementary information Supplementary material is available at Bioinformatics online.
doi_str_mv 10.1093/bioinformatics/btz136
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subjects Applications Notes
title metagenomeFeatures: an R package for working with 16S rRNA reference databases and marker-gene survey feature data
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