detectOutlier {lumi}R Documentation

Detect the outlier sample (or gene)

Description

Usage

detectOutlier(x, metric = "euclidean", standardize = TRUE, Th = 2, ifPlot = FALSE)

Arguments

x a LumiBatch object, ExpressionSet object or a matrix with each column corresponding to a sample or other profile
metric the distance matric
standardize standardize the profile or not
Th the threshold of outlier,
ifPlot to plot the result (as a hierarchical tree) or not

Details

The current outlier detection is based on the distance from the sample to the center (average of all samples). The assumption of the outlier detection is that there is only one single cluster and the distance from the sample to the center is Gaussian distributed.

The outlier is detected when its distance to the center is larger than a certain threshold. The threshold is calculated as Th * median distances to the center.

The profile relations can be visualized as a hierarchical tree.

Value

Plot the results or return the outlier (a logic vector) with the distance matrix and threshold as attributes.

Author(s)

Pan Du

See Also

lumiQ

Examples

## load example data
data(example.lumi)

## detect the outlier (Further improvement needed.)
temp <- detectOutlier(example.lumi, ifPlot=TRUE)


[Package lumi version 1.2.0 Index]