microbial

microbial Build status Code Size:

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.

Installation

library(devtools)
install_github("guokai8/microbial")

Quick tour

library(microbial)

Functions

# 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_aov

Note

The microbial package was bulit based on the dada2 and phyloseq. The package is still under development. New functions will be provided soon.

Contact information

For any questions please contact guokai8@gmail.com