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]