pvaluePlot {PAA} | R Documentation

## Draw a p-value plot.

### Description

Draws a p-value plot to visualize the p-values for all features stored in a `EList` or `EListRaw` object.

### Usage

    pvaluePlot(elist=NULL, group1=NULL, group2=NULL, log=NULL, method="tTest",
    output.path=NULL, tag="", mMs.matrix1=NULL, mMs.matrix2=NULL, above=1500,
    between=400, adjust=FALSE)

### Arguments

`elist` | `EList` or `EListRaw` object (mandatory).
`group1` | vector of column names for group 1 (mandatory).
`group2` | vector of column names for group 2 (mandatory).
`log` | indicates whether the data is in log scale (mandatory; note: if TRUE log2 scale is expected).
`method` | method for p-value computation: `"tTest"` or `"mMs"`. Default is `"tTest"`.
`output.path` | string indicating a path for saving the plot (optional).
`tag` | string that can be used for tagging the saved plot (optional).
`mMs.matrix1` | precomputed M score reference matrix (see `mMsMatrix()`) for group 1 (mandatory when method = "mMs").
`mMs.matrix2` | precomputed M score reference matrix (see `mMsMatrix()`) for group 2 (mandatory when method = "mMs").
`above` | M score above parameter (integer). Default is `"1500"`.
`between` | M score between parameter (integer). Default is `"400"`.
`adjust` | logical indicating whether p-values should be adjusted. Default is `FALSE`.

### Details

This function takes an `EList` or `EListRaw` object and the corresponding column name vectors to draw a plot of p-values for all features stored in `elist` (sorted in increasing order and in log2 scale). The p-value computation method (`"tTest"` or `"mMs"`) can be set via the argument `method`. Furthermore, when `adjust=TRUE` adjusted p-values (method: Benjamini & Hochberg, 1995, computed via `p.adjust()`) will be used. When an output path is defined (via `output.path`) the plot will be saved as a tiff file.

### Value

No value is returned.

### Author(s)

Michael Turewicz, michael.turewicz@rub.de

### Examples

    cwd <- system.file(package="PAA")
    load(paste(cwd, "/extdata/Alzheimer.RData", sep=""))
    elist <- elist[elist$genes$Block < 10,]
    c1 <- paste(rep("AD",20), 1:20, sep="")
    c2 <- paste(rep("NDC",20), 1:20, sep="")
    pvaluePlot(elist=elist, group1=c1, group2=c2, log=FALSE, method="tTest",
     tag="_tTest", adjust=FALSE)

[Package PAA version 1.16.0 Index]