Name Mode Size
R 040000
inst 040000
man 040000
tests 040000
vignettes 040000
.Rbuildignore 100644 0 kb
.gitignore 100644 0 kb
DESCRIPTION 100644 2 kb
NAMESPACE 100644 1 kb 100644 0 kb 100644 2 kb
## 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 ```r # install from GitHub: devtools::install_github("gitlzg/IFAA") ``` ```r # install from Bioconductor: if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("IFAA") ```r ## Usage Use sample datasets to run `IFAA()` function. ```r # Detailed instructions on the package are provided in the manual and vignette library(IFAA) library(SummarizedExperiment) data(dataM) dim(dataM) dataM[1:5, 1:8] data(dataC) dim(dataC) dataC[1:3, ] ## Merge microbiome data and covariate data by id, to avoid unmatching observations. data_merged<-merge(dataM,dataC,by="id",all=FALSE) ## Seperate microbiome data and covariate data, drop id variable from microbiome data dataM_sub<-data_merged[,colnames(dataM)[!colnames(dataM)%in%c("id")]] dataC_sub<-data_merged[,colnames(dataC)] ## Create SummarizedExperiment object test_dat<-SummarizedExperiment(assays=list(MicrobData=t(dataM_sub)), colData=dataC_sub) ## If you already have a SummarizedExperiment format data, you can ## ignore the above steps. results <- IFAA(experiment_dat = test_dat, testCov = c("v1"), ctrlCov = c("v2","v3"), fdrRate = 0.05) ``` Once the analysis is done, you can extract the regression coefficients along with 95% confidence intervals using this command: ```r summary_res<-results$full_results ``` Use sample datasets to run `MZILN()` function. ```r results <- MZILN(experiment_dat=test_dat, targetTaxa = "rawCount18", refTaxa=c("rawCount11"), allCov=c("v1","v2","v3"), fdrRate=0.15) ``` Regression results including confidence intervals can be extracted in the following way: ```r results$full_results ``` ## 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