In songbiostat/MiAF: Microbiome Adaptive Fisher Test

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MiAF

The goal of MiAF is to test for overall association between the composition of a microbial community and a host phenotype of interest (e.g. disease status) with/without covariate adjustments. In this package, we construct a novel community-level test, named MiAF, by adaptively combining p-values from OTU-level (univariate) tests.

Installation

library(devtools)
install_github("songbiostat/MiAF")

Arguments

Y: a numeric vector for continuous or binary responses.
X: a matrix of the OTU table. Row - samples, column - OTUs.
tree: a rooted phylogenetic tree of R class "phylo".
cov: a data frame/matrix for covariate adjustment Row - samples, column - covariates.
model: "gaussian" is for the linear regression model (continuous); "binomial" is for the logistic regression model (binary).
n.perm: the number of permutations.

Values

UniFrac: unweighted UniFrac-like test p-value.
wUniFrac: weighted UniFrac-like test p-value.
UniFrac5: generalized UniFrac-like test p-value.
tip.abun: leaf-nodes-only test p-value.
com: p-value of MiAF test that combines p-values of the above four tests.
select:a list of selected associated taxa.
- lower: under-presented taxa based on lower-tail p-values.
- upper: over-presented taxa based on upper-tail p-values.

Example

library(MiAF)
library(GUniFrac)
data(throat.otu.tab)
data(throat.meta)
data(throat.tree)

y <- as.numeric(throat.meta$SmokingStatus == 'Smoker')
gender <- as.numeric(throat.meta$Sex == 'Female')
zcov <- as.matrix(gender)
MiAF(Y = y, X = throat.otu.tab, tree = throat.tree, cov = zcov, model = "binomial", n.perm = 999)