plotCIs {qusage} | R Documentation

## Plot Pathway Mean and Confidence Intervals

### Description

Functions for plotting the mean and confidence intervals of a set of pathways.

### Usage

    plotCIs(QSarray,
            path.index=1:numPathways(QSarray),
            sort.by=c("mean","p","none"),
            lowerBound=0.025,
            upperBound=1-lowerBound,

            col=NULL,
            use.p.colors=TRUE,
            p.breaks=NULL,
            p.adjust.method = "fdr",
            addLegend=use.p.colors,
            lowerColorBar="none",
            lowerColorBar.cols=NULL,

            addGrid=TRUE,
            x.labels=NULL,
            cex.xaxis=1,
            shift=0.0,

            add=FALSE,
            ylim=NULL, xlim=NULL,
            ylab=NULL, xlab=NULL,
            main=NULL,
            sub=NULL,
            type="p",
            ...
            )

### Arguments

`QSarray` | QSarray object
`path.index` | vector describing which pathways to plot. Can either be numeric or a character vector containing the names of the pathways to plot.
`sort.by` | One of c("mean","p","none") indicating the order that the pathways should be plotted in. If "none", the pathways will not be reordered, and the order specified in path.index will be maintained
`lowerBound, upperBound` | numeric indicating the lower and upper bounds of the confidence intervals. Default is for a 95% confidence interval.
`col` | an optional vector indicating the color for the points. If `use.p.colors=FALSE` is specified, these colors will also be used for the error bars.
`use.p.colors` | logical indicating whether error bars should be colored based on the significance of the p-value.
`p.breaks` | a vector indicating where the breaks in the p-value color scheme should be. By default, breaks will be at 0.001, 0.005, 0.01, 0.05, & 0.1
`p.adjust.method` | The method to use to adjust the p-values. Must be one of the methods in `p.adjust.methods`.
`addLegend` | a logical specifying if a legend for the p-value color scheme be plotted
`lowerColorBar` | Options for plotting a color bar below each point. Automatically generated color bars have not yet been implemented, but custom bars can be created using the "lowerColorBar.cols" parameter.
`lowerColorBar.cols` | a vector of colors to plot as a bar below each point.
`addGrid` | Should guiding dashed lines be plotted?
`x.labels` | character vector of the same length as `path.index` giving the names of the pathways. By default, will use the names stored in QSarray.
`cex.xaxis` | set cex parameter seperately for x axis label
`shift` | a number between 0 and 1 decribing the amount to shift points with respects to the guiding lines and axis labels. Useful when `add=TRUE`
`add` | logical indicating whether a new plot should be created. If `FALSE`, a new plot will be generated.
`xlim, ylim, xlab, ylab, main, sub, type,...` | parameters to be passed on to `plot`

### Details

This function uses the data produced by `aggregateGeneSet` to plot the means and confidence intervals of the gene sets in `QSarray`. By default, the gene sets will be ordered by decreasing mean, and the 95% confidence intervals of each point (as calculated by calcBayesCI) will be added. To specify a different order, `sort.by` must be set to `"none"`, and the order specified by `path.index` will be used.

The points in the plot can be optionally color-coded by the significance of the (corrected) p-values. The p-values are adjusted using R's built in `p.adjust` method, which uses the `p.adjust.method` parameter to determine the algorithm being used. The colors of the points are based on the breaks specified in `p.breaks`. By default, more significant p-values will be plotted in bright red/green. If `use.p.colors` is specified and `addLegend=TRUE`, a legend describing the p-values will be added to the top left corner of the plot. Alternatively, if you want to specify the colors of the points individually, you can provide a vector of colors to the `col` parameter.

The `plotCIs` function can also add a color bar along the bottom of the plot to provide additional information about the pathways. We are currently working on implementing various metrics which can be added automatically using the `lowerColorBar` parameter, but in the mean time, the bar can be added manually by providing a vector of colors the same length as `path.index` to the `lowerColorBar.cols` parameter.

### Examples

    ##create example data
      eset = matrix(rnorm(500*20),500,20, dimnames=list(1:500,1:20))
      labels = c(rep("A",10),rep("B",10))

      geneSets = list()

    ##create a number of gene sets with varying levels of differential expression.
      for(i in 0:10){
        genes = ((30*i)+1):(30*(i+1))
        eset[genes,labels=="B"] = eset[genes,labels=="B"] + rnorm(1)

        geneSets[[paste("Set",i)]] = genes
      }

    ##calculate qusage results
      results = qusage(eset,labels, "B-A", geneSets)

    ##Plot gene set CIs
      plotCIs(results)

[Package qusage version 2.18.0 Index]