DecisionMap {MSstatsQC} | R Documentation

## A function to create heatmaps to compare performance with user defined performance criteria

### Description

A function to create heatmaps to compare performance with user defined performance criteria

### Usage

    DecisionMap(data = NULL, method = "XmR", peptideThresholdRed = 0.7,
      peptideThresholdYellow = 0.5, L = 1, U = 5, type = "mean",
      title = "heatmap plot", listMean = NULL, listSD = NULL)

### Arguments

`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.

### Value

A heatmap to aggregate results per metric generated from `heatmap.DataFrame` data frame.

### Examples

    # 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)
                     )

[Package MSstatsQC version 2.4.0 Index]