autoRemoveOutlier: Automatically detect outlier samples

In wenbostar/metaX: A flexible and comprehensive software for processing omics data.

Automatically detect outlier samples

Description

Automatically detect outlier samples

Usage

autoRemoveOutlier(para, outTol = 1.2, pcaMethod = "svdImpute",
  valueID = "valueNorm", scale = "none", center = FALSE, ...)

Arguments

para	A metaXpara object
outTol	A factor to define the outlier tolerance, default is 1.2
pcaMethod	See pca in pcaMethods
valueID	The name of the column which will be used
scale	Scaling, see pca in pcaMethods
center	Centering, see pca in pcaMethods
...	Additional parameter

Value

The name of outlier samples

Author(s)

Bo Wen [e-mail]

Examples

para <- new("metaXpara")
pfile <- system.file("extdata/MTBLS79.txt",package = "metaX")
sfile <- system.file("extdata/MTBLS79_sampleList.txt",package = "metaX")
rawPeaks(para) <- read.delim(pfile,check.names = FALSE)
sampleListFile(para) <- sfile
para <- reSetPeaksData(para)
para <- missingValueImpute(para)
rs <- autoRemoveOutlier(para,valueID="value")

wenbostar/metaX documentation built on July 4, 2023, 7:50 p.m.