lpe.paired.default {PLPE}R Documentation

Local Pooled Error Test for Paired Data

Description

This invetigates differential expression for paired high-throughput data.

Usage

## Default S3 method:
lpe.paired(x, design, data.type, q=0.01, probe.ID = NULL, estimator="median", w=0.5, w.estimator="fixed", iseed=1234, ...)  

Arguments

x data matrix
design design matrix; condition index in the first column and pair index in the sceond column
q quantile for intervals of intensities
probe.ID probe set IDs; if NULL, row numbers are assigned.
data.type data type: 'ms' for mass spectrometry data, 'cdna' for cDNA microarray data
estimator specification for the estimator: 'median', 'mean' and 'huber'
w weight paramter between individual variance estimate and pooling variance estimate, 0<= w <=1
w.estimator two approaches to estimate the weight: 'random' or 'fixed'
iseed seed number
... other arguments

Value

design design matrix; condition index in the first column and pair index in the sceond column
data.type data type: 'ms' for mass spectrometry data, 'cdna' for cDNA microarray data
q quantile for intervals of intensities
estimator specification for the estimator: 'median', 'mean' and 'huber'
w.estimator two approaches to estimate the weight: 'random' or 'fixed'
w weight paramter between individual variance estimate and pooling variance estimate, 0<= w <=1
test.out matrix for test results

Author(s)

HyungJun Cho and Jae K. Lee

References

Cho H, Smalley DM, Ross MM, Theodorescu D, Ley K and Lee JK (2007). Statistical Identification of Differentially Labelled Peptides from Liquid Chromatography Tandem Mass Spectrometry, Proteomics, 7:3681-3692.

See Also

lpe.paired

Examples


#LC-MS/MS proteomic data for platelets MPs
library(PLPE)
data(plateletSet)
x <- exprs(plateletSet)
x <- log2(x) 

cond <- c(1, 2, 1, 2, 1, 2)
pair <- c(1, 1, 2, 2, 3, 3)
design <- cbind(cond, pair)

out <- lpe.paired(x, design, q=0.1, data.type="ms")
out$test.out[1:10,]
summary(out)

[Package PLPE version 1.2.0 Index]