ReplaceOutliersByMAD {ABSSeq} | R Documentation

## Replacing outliers by moderated MAD

### Description

Function for replacing the outliers by MAD

### Usage

    ReplaceOutliersByMAD(object, replaceOutlier = TRUE, cutoff = 2,
      baseMean = 100, limitMad = 0.707, spriors = 2, Caseon = TRUE, ...)

### Arguments

`object` | a ABSSeq object with element of 'counts' and 'normMethod', see the constructor functions `ABSDataSet`.
`replaceOutlier` | switch for replacing, default is TRUE.
`cutoff` | cutoff of moderating MAD for outliers, default is 2
`baseMean` | parameter for limiting the trimming at low expression level by baseMean/(sample size), default is 100.
`limitMad` | the minimal prior for moderating MAD, default is set to 0.707, which is usually the highest standard deviation at expression level of 1
`spriors` | prior weight size for prior MAD, default is 2
`Caseon` | switch for dealing with outlier trimming at sample size of 2
`...` | reserved parameters

### Details

Given a matrix of count data, this function replacing the outliers by MAD. Noticely, this function also provides part of parameters for DEs calling. It is called by `callParameter`

### Value

a ABSDataSet object with normalized counts after trimming (replaceOutlier=TRUE) or not (replaceOutlier=FALSE). Use the `excounts` to show it. Use `results` with name 'trimmed' to view the trimming status.

### Examples

    data(simuN5)
    obj <- ABSDataSet(counts=simuN5$counts, groups=factor(simuN5$groups))
    obj <- normalFactors(obj)
    obj <- ReplaceOutliersByMAD(obj)
    head(excounts(obj))
    head(results(obj,c("trimmed")))

[Package ABSSeq version 1.44.0 Index]