lpe.paired.fdr.default: FDR for PLPE

Description

This computes FDR for PLPE.

Usage

"lpe.paired.fdr"(x, obj, n.iter=5, lambda=0.9, ...)

Arguments

data matrix

obj

object created from lpe.paired

n.iter

number of iterations

lambda

numeric vector of probabilities with values in [0,1]

...

other argument

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
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
pi0: estimated proportion of non-null peptides
FDR: matrix for test results including FDRs
...: other arguments

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.

Examples

Run this code


#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.fdr <- lpe.paired.fdr(x,obj=out)
out.fdr$FDR[1:10,]