VarianceBoxplot | R Documentation |
This function is to draw a boxplot of the variance of genes quantified by different number of peptides/PSMs. Red curve indicate DEqMS prior variance.
VarianceBoxplot(fit,n=20, xlab="count", ylab = "log(Variance)", main="")
fit |
an object returned from |
n |
set a number to plot only the genes with count value smaller or equal to n |
xlab |
the title for x axis |
ylab |
the title for y axis |
main |
the title for the figure |
return a plot graphic
Yafeng Zhu
library(ExperimentHub)
eh = ExperimentHub(localHub=TRUE)
query(eh, "DEqMS")
dat.psm = eh[["EH1663"]]
dat.psm.log = dat.psm
dat.psm.log[,3:12] = log2(dat.psm[,3:12])
dat.gene.nm = medianSweeping(dat.psm.log,group_col = 2)
psm.count.table = as.data.frame(table(dat.psm$gene)) # generate PSM count table
rownames(psm.count.table)=psm.count.table$Var1
cond = c("ctrl","miR191","miR372","miR519","ctrl",
"miR372","miR519","ctrl","miR191","miR372")
sampleTable <- data.frame(
row.names = colnames(dat.psm)[3:12],
cond = as.factor(cond)
)
gene.matrix = as.matrix(dat.gene.nm)
design = model.matrix(~cond,sampleTable)
fit1 <- eBayes(lmFit(gene.matrix,design))
# add PSM count for each gene
fit1$count <- psm.count.table[rownames(fit1$coefficients),2]
fit2 = spectraCounteBayes(fit1)
VarianceBoxplot(fit2,xlab="PSM count",main="TMT data PXD004163")
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