RPPanalyzer (version 1.0.2)

calcSuperCurve: Calculates the concentration of serial diluted samples

Description

Calculates the protein concentration of a serial diluted sample stored in an RPPA data list using quantification methods implemented in the SuperCurve package (Coombes et. al, 2009).

Usage

calcSuperCurve(x,model="cobs", method="nlrq", sample.id=c("sample","sample.n"),sel=c("measurement","control"), dilution="dilution", block.design, plot=T)

Arguments

x

RPPA data list with replicates aggregated with median

model

The model used by the SuperCurve package. Has to be either "cobs", "logistic" or "loess".

method

The method used for fitting the model. Has to be "nlrq", "nlrob" or "nls".

sample.id

Attributes to identify the samples

sel

The sample type that should be calculated. Has to be "measurements","control", "neg_control",or "blank".

dilution

Name of the column in the feature data matrix describing the dilution steps of the samples.

block.design

Vector with two elements. Describes how the blocks are arranged on the array. The first element specifies the number of rows, the second the number of columns. The blocks are supposed to be arranged row by row in the grid.

plot

Logical. If true, model fits are plotted

Value

• expression
  matrix with expression values
• error
  matrix with error values
• arraydescription
  data frame with feature data
• sampledescription
  data frame with pheno data

Details

This method is wrapper function to give the user access to the quantification methods implemented in the SuperCurve package. The package can be installed from http://bioinformatics.mdanderson.org/Software/OOMPA/.

References

Coombes et. al, 2009, SuperCurve: SuperCurve Package

Hu et al., Bioinformatics 2007, Non-parametric quantification of protein lysate arrays

Examples

library(RPPanalyzer)
data(ser.dil.samples)

predicted.data <- calcSuperCurve(ser.dil.samples, sel=c("measurement"), block.design=c(1,4))