Residualplot: plot the residuals against the number of quantified...

In yafeng/DEqMS: a tool to perform statistical analysis of differential protein expression for quantitative proteomics data.

Description

This function is to plot the residuals of fit model on the vertical axis and the peptide or PSM count on the horizontal axis.

Usage

Residualplot(fit, xlab="log2(count)",
ylab="Variance(fitted - observed)", main="")

Arguments

fit	an object returned from spectraCounteBayes function
xlab	the title for x axis
ylab	the title for y axis
main	the title for the figure

Value

return a plot graphic

Author(s)

Yafeng Zhu

Examples

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)
    
Residualplot(fit2,xlab="log2(PSM count)",main="TMT data PXD004163")

yafeng/DEqMS documentation built on June 3, 2020, 8:23 p.m.