ABSSeq (version 1.8.0)

ReplaceOutliersByMAD: 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

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.

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

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")))