Package: sparseDOSSA
Type: Package
Title: Sparse Data Observations for Simulating Synthetic Abundance
Version: 1.12.0
Date: 2016-10-28
Author: Boyu Ren<bor158@mail.harvard.edu>, Emma
        Schwager<emma.schwager@gmail.com>, Timothy
        Tickle<ttickle@hsph.harvard.edu>, Curtis Huttenhower
        <chuttenh@hsph.harvard.edu>
Maintainer: Boyu Ren<bor158@mail.harvard.edu>, Emma Schwager
 <emma.schwager@gmail.com>, George
 Weingart<george.weingart@gmail.com>
Description: The package is to provide a model based Bayesian method to
        characterize and simulate microbiome data. sparseDOSSA's model
        captures the marginal distribution of each microbial feature as
        a truncated, zero-inflated log-normal distribution, with
        parameters distributed as a parent log-normal distribution. The
        model can be effectively fit to reference microbial datasets in
        order to parameterize their microbes and communities, or to
        simulate synthetic datasets of similar population structure.
        Most importantly, it allows users to include both known
        feature-feature and feature-metadata correlation structures and
        thus provides a gold standard to enable benchmarking of
        statistical methods for metagenomic data analysis.
License: MIT + file LICENSE
VignetteBuilder: knitr
Suggests: knitr, BiocStyle, BiocGenerics, rmarkdown
Imports: stats, utils, optparse, MASS, tmvtnorm (>= 1.4.10), MCMCpack
biocViews: ImmunoOncology, Bayesian, Microbiome, Metagenomics, Software
RoxygenNote: 5.0.1
git_url: https://git.bioconductor.org/packages/sparseDOSSA
git_branch: RELEASE_3_11
git_last_commit: ab73f59
git_last_commit_date: 2020-04-27
Date/Publication: 2020-04-27
NeedsCompilation: no
Packaged: 2020-04-28 05:17:44 UTC; biocbuild
Built: R 4.0.0; ; 2020-04-28 17:40:33 UTC; windows
