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This package provides a way to estimate and test marginal mediation effects for zero-inflated compositional mediators.
## From GitHub:
::install_github("quranwu/MarZIC") devtools
Detailed instructions can be found in the vignette file.
The example data was built from scratch, with 200 observations and 10 taxon.
library(MarZIC)
## A make up example with 1 taxon and 100 subjects.
set.seed(1)
<- 200
nSub <- 10
nTaxa ## generate covariate of interest X
<- rbinom(nSub, 1, 0.5)
X ## generate mean of each taxon. All taxon are having the same mean for simplicity.
<- exp(-5 + X) / (1 + exp(-5 + X))
mu <- 10
phi
## generate true RA
<-t(sapply(mu,function(x) dirmult::rdirichlet(n=1,rep(x*phi,nTaxa))))
M_taxon
<- exp(-3 + 0.3 * X) / (1 + exp(-3 + 0.3 * X))
P_zero
<- t(sapply(P_zero,function(x) 1-rbinom(nTaxa,1,rep(x,nTaxa))))
non_zero_ind
<-t(apply(M_taxon*non_zero_ind,1,function(x) x/sum(x)))
True_RA
## generate outcome Y based on true RA
<- 1 + 100 * True_RA[,1] + 5 * (True_RA[,1] > 0) + X + rnorm(nSub)
Y
## library size was set to 10,000 for all subjects for simplicity.
<- 10000
libsize
## generate observed RA
<- floor(M_taxon*libsize*non_zero_ind)
observed_AA
<- t(apply(observed_AA,1,function(x) x/sum(x)))
observed_RA colnames(observed_RA)<-paste0("rawCount",seq_len(nTaxa))
## Construct SummerizedExperiment object
<- cbind(Y = Y, X = X, libsize = libsize)
CovData <-
test_dat ::SummarizedExperiment(assays = list(MicrobData = t(observed_RA)), colData = CovData)
SummarizedExperiment
## run the analysis
<- MarZIC(
res Experiment_dat = test_dat,
lib_name = "libsize",
y_name = "Y",
x_name = "X",
num_cores = 1,
mediator_mix_range = 1
)
Once the analysis is done, res
is a list with four
elements, each for NIE\(_1\), NIE\(_2\), NDE, NIE, respectively. The NIE\(_1\), for example, could be extracted
as:
<- res$NIE1_save NIE1
And the significant result could be extracted as:
subset(NIE1,significance == TRUE)
Wu et al.(2022) MarZIC: A Marginal Mediation Model for Zero-Inflated Compositional Mediators with Applications to Microbiome Data. Genes 2022, 13, 1049.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.