Nathan D Olson1,2,3, Nidhi Shah2,3,4, Jayaram Kancherla2,3, Justin Wagner2,3,4, Joseph N Paulson5, Hector Corrada Bravo2,3,4. 1. Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA. 2. Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA. 3. University of Maryland Institute for Advanced Computer Studies, College Park, MD, USA. 4. Department of Computer Science, University of Maryland, College Park, MD, USA. 5. Department of Biostatistics, Product Development, Genentech Inc., South San Francisco, CA, USA.
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. Published by Oxford University Press 2019. This work is written by US Government employees and is in the public domain in the US.
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. Published by Oxford University Press 2019. This work is written by US Government employees and is in the public domain in the US.
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