Description Usage Arguments Value Examples
A function to create heatmaps to compare performance with user defined performance criteria
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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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | # 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")
DecisionMap(data = sampleData, method = "CUSUM", type = "mean",
listMean = list("BestRetentionTime" = 27.78,
"TotalArea" = 35097129,
"MaxFWHM" = 0.28,
"Peak Assymetry" = 0.98),
listSD = list("BestRetentionTime" = 8.19,
"TotalArea" = 34132861,
"MaxFWHM" = 0.054,
"Peak Assymetry" = 0.002)
)
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