themetagenomics: Exploring Thematic Structure and Predicted Functionality of 16s rRNA Amplicon Data

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).

Version: 0.1.0
Depends: R (≥ 3.2.5), Rcpp (≥ 0.11.3)
Imports: ggplot2, lda, lme4 (≥ 1.1.12), Matrix, plotly (≥ 4.5.6), rstan (≥ 2.14.0), scales, shiny (≥ 1.0.0), stats, stats4, stm (≥ 1.1.4)
LinkingTo: Rcpp
Suggests: assertthat, covr, huge, igraph, inline, knitr, networkD3, proxy, rmarkdown, RcppArmadillo, Rtsne, testthat, vegan, viridis
Published: 2017-06-06
Author: Stephen Woloszynek [aut, cre]
Maintainer: Stephen Woloszynek <sw424 at>
License: MIT + file LICENSE
NeedsCompilation: yes
Citation: themetagenomics citation info
Materials: README NEWS
CRAN checks: themetagenomics results


Reference manual: themetagenomics.pdf
Vignettes: Predicting Functional Content
Finding Thematic Structure in the David Dataset
Package source: themetagenomics_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: themetagenomics_0.1.0.tgz
OS X Mavericks binaries: r-oldrel: themetagenomics_0.1.0.tgz


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