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knitr::opts_chunk$set(
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  fig.path = "man/figures/README-",
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ZicoSeq

Overview

ZicoSeq is a permutation-based framework for differential abundance analysis of Zero-inflated Compositional Sequencing data such as microbiome data. Currently, it has the following components:

Winsorization to decrease the influence of outliers.
Posterior sampling to impute zeros based on a beta mixture prior.
Multiple-stage normalization to address compositional effects.
An omnibus test to address diverse taxa-covariate relationships.
Permutation-based FDR control to address taxa correlations and multiple testing

Installation

You can install the released version of ZicoSeq from GitHub with:

# install.packages("devtools")
# install.packages(c("matrixStats", "stats", "permute", "nlme", "vegan", "rmulti"))
devtools::install_github("chloelulu/ZicoSeq")

Example Usage

This is a basic example which shows you how to solve a common problem:

library(ZicoSeq)
#install.packages('GUniFrac')
library(GUniFrac) #This package loaded here is only used for citing the throat data
data(throat.otu.tab)
data(throat.meta)
comm <- t(throat.otu.tab)
meta.dat <- throat.meta

set.seed(123)
zico.obj <- ZicoSeq(meta.dat = meta.dat, comm = comm, grp.name = 'SmokingStatus', adj.name = 'Sex',
        # Filtering criterion
        prev.filter = 0.1, abund.filter = 10,  min.prop = 0, 
        # Winsorization to replace outliers
        is.winsor = TRUE, winsor.qt = 0.97,
        # Posterior sampling
        is.prior = TRUE, prior.dist = c('BetaMix'), post.method = c('sample'), post.sample.no = 25, 
        # Link functions
        link.func = list(function (x) x^0.25, function (x) x^0.5, function (x) x^0.75), stats.combine.func = max,
    # Permutation
        perm.no = 99,  strata = NULL, 
        # Multiple stage normalization
        stage.no = 6, topK = NULL, stage.fdr = 0.75, stage.max.pct = 0.50,  
        # Tree-based FDR control and family-wise error rate control
        is.fwer = FALSE, is.tree.fdr = FALSE, tree = NULL, 
        verbose = TRUE, return.comm = FALSE, return.perm.F = FALSE)

which(zico.obj$p.adj.fdr <= 0.1)