An R package for microbial community analysis with dada2 and phyloseq
This package is developed to enhance the available statistical analysis procedures in R by providing simple functions to analysis and visualize the 16S rRNA data.
library(devtools)
install_github("guokai8/microbial")library(microbial)# You can use processSeq function to do analysis start from fastq files
?processSeq
# You may need to first download the reference database
preRef(ref_db="silva")
# to check the quality of you reads
?plotquality
# calcuate the alpha diversity
data("GlobalPatterns",package="phyloseq")
physeq <- GlobalPatterns
richness(physeq,method=c("Simpson", "Shannon"))
# plot alpha diversity
plotalpha(physeq,method=c("Simpson", "Shannon"),group="SampleType")
# make barplot for relative abundance
phy <- normalize(physeq)
plotbar(phy,level="Phylum")
# plot beta diversity(PCoA)
plotbeta(phy,group="SampleType",distance="bray",method="PCoA")
# perform PERMANOVA test
betatest(phy,group="SampleType",distance="bray")
# do differential analysis with DESeq2
require(phyloseq)
samdf<-as(sample_data(physeq),"data.frame")
samdf$group<-c(rep("A",14),rep("B",12))
sample_data(physeq)<-samdf
res <- difftest(physeq,group="group")
# plot the differential results
plotdiff(res,level="Genus")
# do LEfse analysis
res <- ldamarker(physeq,group="group")
# plot LEfse results
plotLDA(res,group=c("A","B"),lda=5,pvalue=0.05)
# use RandomForest to select markers
res <- biomarker(physeq,group="group")
plotmarker(res,level="Genus")
# do some test
?do_ttest
?do_wilcox
?do_aovThe microbial package was bulit based on the dada2 and phyloseq. The package is still under development. New functions will be provided soon.
For any questions please contact guokai8@gmail.com