findAllOutliers {beadarray} | R Documentation

## Find outliers on array

### Description

Function to find all beads which are outliers for their particular bead type on a given array.

### Usage

    findAllOutliers(BLData, array, log=FALSE, n=3, what="G")

### Arguments

`BLData` | a BeadLevelList object
`array` | numeric value specifying which array we want to find outliers on
`log` | if TRUE the log2 intensities will be used to calculate outliers
`n` | Specify a cut-off for outliers as n median absolute deviations (MADs) from the median. The default value is 3
`what` | character string specifying which intensities to use. Possibilities are `"G"`, `"Gb"` for single channel data and `"G"`, `"Gb"`, `"R"` and `"Rb"` for two-colour data

### Details

We find the outliers for each bead type on the array in turn using the `findBeadStatus` function and keep a list of the outliers found. By default, outliers for a particular bead type are determined using a 3 MAD cut-off from the median.

### Value

numeric vector giving the row indices of BLData (in the range 1 to total number of beads on the array) of all the beads that are outliers for their bead type.

### Author(s)

Mark Dunning

### See Also

`findBeadStatus`

### Examples

    data(BLData)
    # how many outliers are there on the original scale?
    length(findAllOutliers(BLData, 1))
    # how many outliers are there on the log2-scale?
    length(findAllOutliers(BLData, 1, log=TRUE)) #
    # how many outliers are there using a 4 MAD
    # cut-off from the median?
    length(findAllOutliers(BLData, 1, n=4))

[Package beadarray version 1.6.0 Index]