odm-package: Functions for detecting outlying observations in (multiple)...
In sooheang/OutlierDM: Outlier Detection for Multiplicative High-throughput Data

Description Details Author(s) References See Also Examples

This package provides outlier detection algorithms for multiple replicated high-throughput data, especially in the field of mass spectrometry.

Package:	OutlierDM
Type:	Package
Version:	1.1-0
Date:	2014-12-31
License:	GPL version 3
LazyLoad:	no

Soo-Heang Eo <eo.sooheang@gmail.com> and HyungJun Cho <hj4cho@korea.ac.kr>

Maintainer: Soo-Heang Eo <eo.sooheang@gmail.com>

Cho H, and Eo, S-H. (2014). Outlier Detection for Mass-Spectrometry Data. Submitted.

Eo, S-H, Pak, D, Choi, J, and Cho, H. (2012). Outlier Detection for Multiplicative High-throughput Data. BMC Research Notes, 5, 1–6.

Cho et al. (2008). OutlierD: an R package for outlier detection using quantile regression on mass spectrometry data. Bioinformatics, 24(6), 882–884.

Min et al. (2007). Ultrahigh-pressure dual online solid phase extraction/capillary reverse-phase liquid chromatography/tandem mass spectrometry (DO-SPE/cRPLC/MS/MS): A versatile separation platform for high-throughput and highly sensitive proteomic analyses. ELECTROPHORESIS, 28, 1012–1021.

odm, odm.control, quantreg

## Not run: 
data(lcms3)

## Fit projection approaches
fit.proj.const <- odm(lcms3, method="constant")
fit.proj.linear <- odm(lcms3, method="linear")
fit.proj.nonlin <- odm(lcms3, method="nonlin")
fit.proj.nonpara <- odm(lcms3, method="nonpar", lbda = 1)

par(mfrow = c(2,2))
plot(fit.proj.const, main = "Constant")
plot(fit.proj.linear, main = "Linear")
plot(fit.proj.nonlin, main = "NonLinear")
plot(fit.proj.nonpara, main = "Nonparametric")

## Fit pairwise OutlierD algorithm
fit0 <- odm(lcms3, type = "pair")
plot(fit0)

## End(Not run)