A means to explore the structure of 16S rRNA surveys using a Structural Topic Model coupled with functional prediction. The user provides an abundance table, sample metadata, and taxonomy information, and themetagenomics infers associations between topics and sample features, as well as topics and predicted functional content. Functional prediction can be accomplished via Tax4Fun (for Silva references) and PICRUSt (for GreenGeenes references).
themetagenomics provides functions to explore topics generated from 16S rRNA sequencing information on both the abundance and functional levels. It also provides an R implementation of PICRUSt and wraps Tax4fun, giving users a choice for their functional prediction strategy.
Stephen Woloszynek, Zhengqiao Zhao, Gideon Simpson, Joshua Chang Mell, and Gail Rosen. Gauging the use of topic models as a means to understand microbiome data structure. TBD, 2017
install.packages('themetagenomics')# To install the developmental version via Github:# install.packages('devtools')devtools::install_github('EESI/themetagenomics',build_vignettes=TRUE)
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