sim.meta

<p>This data set includes 100 simulated samples from 50 subjects, with two samples from each subject. 
The metadata contain subject IDs and data from four variables, two (X.between and Y.between) varying between subjects 
and two (X.within and Y.within) varying within subjects.</p>

datasets

A single analysis path that includes distance-based ordination, global tests of any effect of the microbiome, and tests of the effects of individual taxa with false-discovery-rate (FDR) control. It accommodates both continuous and discrete covariates as well as interaction terms to be tested either singly or in combination, allows for adjustment of confounding covariates, and uses permutation-based p-values that can control for sample correlations. It can be applied to transformed data, and an omnibus test can combine results from analyses conducted on different transformation scales. It can also be used for testing presence-absence associations based on infinite number of rarefaction replicates, testing mediation effects of the microbiome, analyzing censored time-to-event outcomes, and for compositional analysis by fitting linear models to centered-log-ratio taxa count data.

Yi-Juan Hu

Testing Hypotheses About the Microbiome using the Linear
Decomposition Model

Glen A Satten

sim.meta function

<p>A data frame with 100 observations on 5 variables.</p>

sim.meta: Metadata of the simulated microbiome samples

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