?hclust
rpkm.dat1<-drop.var(rpkm.tpose, min.fo=8)
source("/Users/Steven/Desktop/Emma's files/biostats.R")
rpkm.dat1<-drop.var(rpkm.tpose, min.fo=8)
setwd("/Users/Steven/Desktop/Emma's files/RNA-Seq RPKM")
rpkm.dat<-read.csv('RPKM all oysters rounded.csv', header=T, row.names=1)
rpkm.df<-as.data.frame(rpkm.dat)
rpkm.tpose<-t(rpkm.df)
rpkm.dat1<-drop.var(rpkm.tpose, min.fo=8)
str(rpkm.dat1)
str(rpkm.tpose)
str(rpkm.dat)
rpkm.dat1<-drop.var(rpkm.dat, min.fo=8)
str(rpkm.dat1)
is.integer(rpkm.tpose[1,1])
rpkm.tpose[1,1]
is.integer(rpkm.dat[1,1])
is.factor(rpkm.tpose[1,1])
as.matrix(rpkm.tpose)
rpkm.mat<-as.matrix(rpkm.tpose)
str(rpkm.mat)
rpkm.tra<-(rpkm.tpose+1)
rpkm.tra<-data.trans(rpkm.tra, method='log', plot=F)
rpkm.bray<-vegdist(rpkm.tra, method='bray')
library(vegan)
rpkm.bray<-vegdist(rpkm.tra, method='bray')
rpkm.clust<-hclust(rpkm.bray, method='average')
plot(rpkm.clust, main='Average-Linkage Dendrogram, RPKM all')
rpkm.nmds<-metaMDS(rpkm.tra, distance='bray', k=2, trymax=100)
ordiplot(rpkm.nmds, choices=c(1,2), type='text', display='sites', xlab='Axis 1', ylab='Axis 2')
treatment<-as.factor(c(rep("high", 4), rep("low", 4)))
ordihull(rpkm.nmds, treatment, label=T)