outlyx {wateRmelon} | R Documentation

## 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=TRUE, ...)

### 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.

### Note

May perform poorly on normalized data

### Author(s)

Tyler Gorrie-Stone - tgorri@essex.ac.uk

### Examples

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

[Package wateRmelon version 1.28.0 Index]