imageNA2 {MSnbase} | R Documentation

## NA heatmap visualisation for 2 groups

### Description

Produces a heatmap after reordring rows and columsn to highlight missing value patterns.

### Usage

    imageNA2(object, pcol, Rowv, Colv = TRUE, useGroupMean = FALSE,
      plot = TRUE, ...)

### Arguments

`object` | An instance of class MSnSet
`pcol` | Either the name of a phenoData variable to be used to determine the group structure or a factor or any object that can be coerced as a factor of length equal to nrow(object). The resulting factor must have 2 levels. If missing (default) `image(object)` is called.
`Rowv` | Determines if and how the rows/features are reordered. If missing (default), rows are reordered according to `order((nNA1 + 1)^2/(nNA2 + 1))`, where NA1 and NA2 are the number of missing values in each group. Use a vector of numerics of feautre names to customise row order.
`Colv` | A `logical` that determines if columns/samples are reordered. Default is `TRUE`.
`useGroupMean` | Replace individual feature intensities by the group mean intensity. Default is FALSE.
`plot` | A `logical` specifying of an image should be produced. Default is `TRUE`.
`...` | Additional arguments passed to `image`.

### Value

Used for its side effect of plotting. Invisibly returns Rovw and Colv.

### Author(s)

Laurent Gatto, Samuel Wieczorek and Thomas Burger

### Examples

    library("pRolocdata")
    library("pRoloc")
    data(dunkley2006)
    pcol <- ifelse(dunkley2006$fraction <= 5, "A", "B")
    nax <- makeNaData(dunkley2006, pNA = 0.10)
    exprs(nax)[sample(nrow(nax), 30), pcol == "A"] <- NA
    exprs(nax)[sample(nrow(nax), 50), pcol == "B"] <- NA
    MSnbase:::imageNA2(nax, pcol)
    MSnbase:::imageNA2(nax, pcol, useGroupMean = TRUE)
    MSnbase:::imageNA2(nax, pcol, Colv = FALSE, useGroupMean = FALSE)
    MSnbase:::imageNA2(nax, pcol, Colv = FALSE, useGroupMean = TRUE)

[Package MSnbase version 2.4.2 Index]