Overview

IFAA is a novel approach to make inference on the association of covariates with the absolute abundance (AA) of microbiome in an ecosystem.

Installation

# install from GitHub:
devtools::install_github("gitlzg/IFAA")

Usage

Use sample datasets to run IFAA() function.

# Detailed instructions on the package are provided in the manual and vignette
library(IFAA)
 
data(dataM)
data(dataC)
 
results <- IFAA(MicrobData = dataM,
                CovData = dataC,
                linkIDname = "id",
                testCov = c("v1", "v2"),
                ctrlCov = c("v3"),
                nRef = 4,
                nPermu = 4,
                bootB = 5)

Once the analysis is done, you can extract the regression coefficients along with 95% confidence intervals using this command:

results$analysisResults$estByCovList

The function can also take csv or tsv data files directly by reading the file directory paths using the first two arguments:

M="pathToTheCsvFile/microbiomeData.csv" 
# or 
M="pathToTheTsvFile/microbiomeData.tsv"

C="pathToTheCsvFile/covariatesData.csv" 
# or 
C="pathToTheTsvFile/covariatesData.tsv"

results=IFAA(MicrobData=M,CovData=C,...)

Use sample datasets to run MZILN() function.

results <- MZILN(MicrobData = dataM,
                 CovData = dataC,
                 linkIDname = "id",
                 allCov = c("v1","v2","v3"),
                 refTaxa=c("rawCount11")
                 )

Regression results including confidence intervals can be extracted in the following way:

results$analysisResults$estByRefTaxaList$rawCount11$estByCovList

References

• Zhigang Li, Lu Tian, A. James O'Malley, Margaret R. Karagas, Anne G. Hoen, Brock C. Christensen, Juliette C. Madan, Quran Wu, Raad Z. Gharaibeh, Christian Jobin, Hongzhe Li (2020) IFAA: Robust association identification and Inference For Absolute Abundance in microbiome analyses. arXiv:1909.10101v3

• Zhigang Li, Katherine Lee, Margaret Karagas, Juliette Madan, Anne Hoen, James O’Malley and Hongzhe Li (2018 ) Conditional regression based on a multivariate zero-inflated logistic normal model for modeling microbiome data. Statistics in Biosciences 10(3):587-608