.makeQCPlot {MSstats}R Documentation

Make QC plot

Description

To illustrate the quantitative data after data-preprocessing and quality control of MS runs, dataProcessPlots takes the quantitative data from function (dataProcess) as input and automatically generate three types of figures in pdf files as output : (1) profile plot (specify "ProfilePlot" in option type), to identify the potential sources of variation for each protein; (2) quality control plot (specify "QCPlot" in option type), to evaluate the systematic bias between MS runs; (3) mean plot for conditions (specify "ConditionPlot" in option type), to illustrate mean and variability of each condition per protein.

Usage

.makeQCPlot(
  input,
  all_proteins,
  y.limdown,
  y.limup,
  x.axis.size,
  y.axis.size,
  text.size,
  text.angle,
  legend.size,
  label.color,
  cumGroupAxis,
  groupName,
  lineNameAxis,
  yaxis.name
)

Arguments

input

data.table

all_proteins

character vector of protein names

x.axis.size

size of x-axis labeling for "Run" in Profile Plot and QC Plot, and "Condition" in Condition Plot. Default is 10.

y.axis.size

size of y-axis labels. Default is 10.

text.size

size of labels represented each condition at the top of graph in Profile Plot and QC plot. Default is 4.

text.angle

angle of labels represented each condition at the top of graph in Profile Plot and QC plot or x-axis labeling in Condition plot. Default is 0.

legend.size

size of feature legend (transition-level or peptide-level) above graph in Profile Plot. Default is 7.

Details

The input of this function is the quantitative data from function dataProcess.

Examples

# Consider quantitative data (i.e. QuantData) from a yeast study with ten time points of interests, 
# three biological replicates, and no technical replicates which is a time-course experiment. 
# The goal is to provide pre-analysis visualization by automatically generate two types of figures 
# in two separate pdf files. 
# Protein IDHC (gene name IDP2) is differentially expressed in time point 1 and time point 7, 
# whereas, Protein PMG2 (gene name GPM2) is not.

QuantData<-dataProcess(SRMRawData, use_log_file = FALSE)
head(QuantData$FeatureLevelData)
# Profile plot
dataProcessPlots(data=QuantData,type="ProfilePlot")
# Quality control plot 
dataProcessPlots(data=QuantData,type="QCPlot")	
# Quantification plot for conditions
dataProcessPlots(data=QuantData,type="ConditionPlot")


[Package MSstats version 4.0.1 Index]