DecisionMap {MSstatsQC} | R Documentation |
A function to create heatmaps to compare performance with user defined performance criteria
DecisionMap( data = NULL, method = "XmR", peptideThresholdRed = 0.7, peptideThresholdYellow = 0.5, L = 1, U = 5, type = "mean", title = "heatmap plot", listMean = NULL, listSD = NULL )
data |
Comma-separated (*.csv), QC file format. It should contain a Precursor column and the metrics columns. |
method |
It is either "CUSUM" or "XmR" |
peptideThresholdRed |
Is a threshold that marks percentage of peptides above it red on the heatmap. Defaults to 0.7 |
peptideThresholdYellow |
Is a threshold that marks percentage of peptides above it and below the peptideThresholdRed, yellow on the heatmap. Defaults to 0.5 |
L |
Lower bound of the giude set. Defaults to 1 |
U |
Upper bound of the guide set. Defaults to 5 |
type |
can take two values, "mean" or "dispersion". Defaults to "mean" |
title |
the title of the plot. Defaults to "heatmap plot" |
listMean |
List of the means for the metrics. If you don't know the means leave it as NULL and they will be calculated automatically by using L and U. The default is NULL. |
listSD |
List of the standard deviations for the metrics. If you don't know the standard deviations leave it as NULL and they will be calculated automatically by using L and U. The default is NULL. |
A heatmap to aggregate results per metric generated from heatmap.DataFrame
data frame.
# First process the data to make sure it's ready to use sampleData <- DataProcess(S9Site54) head(sampleData) # Draw Decision maker plot DecisionMap(data = sampleData, method = "CUSUM") DecisionMap(data = sampleData, method = "CUSUM", type = "variability") DecisionMap(data = sampleData, method = "XmR") DecisionMap(data = sampleData, method = "XmR", type = "variability")