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 1.10.0 Index]