findAllOutliers {beadarray} | R Documentation

## Find outliers on a given strip/array

### Description

Function to find all beads which are outliers for their particular bead type on a given strip/array using Illumina's standard outlier detection method.

### Usage

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

### Arguments

`BLData` | `BeadLevelList`
`array` | integer specifying which strip/array we want to find outliers on
`log` | if TRUE the intensities will be calculated on the log2 scale. Otherwise un-logged data is used.
`n` | numeric value defining a cut-off for the number of median absolute deviations (MADs) from the median to use for determining outliers. The default value is 3.
`what` | character string specifying which intensities to use. See `getArrayData` for a list of possibilities.
`usewts` | if TRUE, then beads with weights below 1 will be discarded prior to analysis.

### Details

We find the outliers for each bead type on the array in turn using the `findBeadStatus` function and store the indices 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 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 1.12.1 Index]