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wateRmelon (version 1.16.0)

outlyx: Identify Outliers within Methylumi and Minfi packaged objects

Description

Seeks to identify outliers based on multiple (currently 2) outlier detection methods for methylumi and minfi packaged objects.

Usage

outlyx(x, iqr=TRUE, iqrP=2, pc=1, mv=TRUE, mvP=0.15, plot=FALSE, ...)

Arguments

x
A MethyLumiSet, MethylSet, RGChannelSet object or matrix containing raw betas.
iqr
If TRUE, the outliers based on interquartile ranges will be determined
iqrP
The number of interquartile ranges outliers are to be identified from designated principle component.
pc
Desired principal component for outlier identification - only used if other principal components want to be discriminated, only used for IQR outlier detection.
mv
If TRUE, the outliers will detected using pcout
mvP
Arbitrary cut-off point for identifying outliers via pcout
plot
If TRUE, alongside regular output, a plot will be constructed displaying relative 'location' of each sample. Outliers are those that fall within the highlighted regions.
...
Additional arguments passed to pcout

Value

Returns a dataframe of TRUE/FALSE per sample. Where TRUE is outlying.

Examples

Run this code
 library(wateRmelon)
 data(melon)
 outliers <- outlyx(melon,iqr=TRUE, iqrP=2, pc=1,
                    mv=TRUE, mvP=0.15, plot=TRUE)

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