calcLinear: Calculates sample concentrations using linear model fit

In RPPanalyzer: Reads, Annotates, and Normalizes Reverse Phase Protein Array Data

Calculates sample concentrations using linear model fit

Description

calculates sample concentrations of a RPPA data set, using parameter of a linear model fitted to the dilution series.

Usage

calcLinear(x, sample.id = c("sample", "sample.n"), dilution = "dilution"
, method = "quantreg", plot = F, detectionLimit = T)

Arguments

x	List containing background corrected RPPA data set
sample.id	character vector refering to column names from which samples can be separated
dilution	column name from the column in feature data that describes the dilution steps of each sample
method	character string describing the method used for the linear fit
plot	logical. If true dilution curves are plotted
detectionLimit	logical. If true model is fitted on dilution steps above the detection limit. If false, all data points are used to fit the model

Value

expression	matrix with protein expression data
dummy	matrix with protein expression data
arraydescription	data frame with feature data
sampledescription	data frame with pheno data

Note

for calculation of serial diluted samples only

Author(s)

Heiko Mannsperger <[e-mail]>,Stephan Gade <[e-mail]>

Examples

## Not run: 
library(RPPanalyzer)
data(ser.dil.samples)

predicted.data <- calcLinear(ser.dil.samples,sample.id=c("sample","sample.n"),
dilution="dilution")

## End(Not run)

RPPanalyzer documentation built on Aug. 28, 2023, 5:07 p.m.