OutlierD: Outlier detection using quantile regression on the M-A scatterplots of high-throughput data
Version 1.40.0

This package detects outliers using quantile regression on the M-A scatterplots of high-throughput data.

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AuthorHyungJun Cho <hj4cho@korea.ac.kr>
Bioconductor views Microarray
Date of publicationNone
MaintainerSukwoo Kim <s4kim@korea.ac.kr>
LicenseGPL (>= 2)
Version1.40.0
URL http://www.korea.ac.kr/~stat2242/
Package repositoryView on Bioconductor
InstallationInstall the latest version of this package by entering the following in R:
source("https://bioconductor.org/biocLite.R")
biocLite("OutlierD")

Man pages

lcms: LCMS data
OutlierD: Outlier dectection using quantile regression on the M-A...

Functions

First.lib Source code
OutlierD Man page Source code
lcms Man page
quant.const Source code
quant.linear Source code
quant.nonlin Source code
quant.nonpar Source code

Files

DESCRIPTION
NAMESPACE
R
R/OutlierD.R
build
build/vignette.rds
data
data/lcms.RData
inst
inst/doc
inst/doc/OutlierD.R
inst/doc/OutlierD.Rnw
inst/doc/OutlierD.pdf
man
man/OutlierD.Rd
man/lcms.Rd
vignettes
vignettes/OutlierD.Rnw
OutlierD documentation built on May 20, 2017, 10:45 p.m.