This package is developed to simulate microbiome data for longitudinal
differential abundance analyses. Microbiome data have a variety of
features that make typical simulation methods inappropriate. For an
in-depth description of the types of problems this simulation package is
designed to solve, plus basics of the functionality please refer to the
F1000 manuscript
f1000research.20660.2.
Installation
To install the microbiomeDASim package the latest release version is
available from Bioconductor
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("microbiomeDASim")
Alternatively to use the latest development version from Bioconductor
use the following commands
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("microbiomeDASim", version="devel")
Examples
An interactive examples for how to simulate data from a multivariate
normal distribution and fit a trend line using
metagenomeSeq::fitTimeSeries
are available in the inst/scripts directory.
This notebook can be run interactively using Google Collab by clicking
the “Open in Colab” marker at the top of the notebook.
Microbiome Differential Abundance Simulation
This package is developed to simulate microbiome data for longitudinal differential abundance analyses. Microbiome data have a variety of features that make typical simulation methods inappropriate. For an in-depth description of the types of problems this simulation package is designed to solve, plus basics of the functionality please refer to the F1000 manuscript f1000research.20660.2.
Installation
To install the
microbiomeDASimpackage the latest release version is available from BioconductorAlternatively to use the latest development version from Bioconductor use the following commands
Examples
An interactive examples for how to simulate data from a multivariate normal distribution and fit a trend line using metagenomeSeq::fitTimeSeries are available in the
inst/scriptsdirectory.This notebook can be run interactively using Google Collab by clicking the “Open in Colab” marker at the top of the notebook.