ArrayOutliers-methods {arrayMvout}R Documentation

ArrayOutliers – wrapper for platform-specific multivariate outlier detection for expression arrays

Description

wraps functions that perform multivariate outlier detection on dimension-reduced QA statistics of expression arrays

Methods

data = "ANY", alpha = "missing", alphaSeq = "missing"
fails; tells user that alpha is obligatory parameter
data = "AffyBatch", alpha = "numeric", alphaSeq = "ANY"
performs calibrated multivariate outlier detection on an AffyBatch instance using various affy-specific QA parameters
data = "LumiBatch", alpha = "numeric", alphaSeq = "ANY"
performs calibrated multivariate outlier detection on an LumiBatch instance using various illumina-specific QA parameters
data = "data.frame", alpha = "numeric", alphaSeq = "ANY"
performs calibrated outlier detection on QA statistics housed in data.frame – all columns of the data entity must be numeric QA statistics for the arrays.

Examples

example(ArrayOutliers)

[Package arrayMvout version 1.0.0 Index]