normPCR: Normalization of real-time quantitative RT-PCR data

In SLqPCR: Functions for analysis of real-time quantitative PCR data at SIRS-Lab GmbH

Description

This function can be used to normalize real-time quantitative RT-PCR data.

Usage

normPCR(relData, HKs, method = "Vandesompele", na.rm = FALSE)

Arguments

relData	matrix or data.frame containing relative quantities (genes in columns)
HKs	integer, column numbers of housekeeping genes
method	method for the computation
na.rm	a logical value indicating whether NA values should be stripped before the computation proceeds.

Details

This function can be used to normalize real-time quantitative RT-PCR data. The default method "Vandesompele" was proposed by Vandesompele et al. (2002).

Currently, only the method by Vandesompele et al. (2002) is implemented.

Value

Normalized expression data

Author(s)

Dr. Matthias Kohl (SIRS-Lab GmbH) [e-mail]

References

Jo Vandesompele, Katleen De Preter, Filip Pattyn et al. (2002). Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biology 2002. 3(7):research0034.1-0034.11. http://genomebiology.com/2002/3/7/research/0034/

Examples

data(SLqPCRdata)
relData <- apply(SLqPCRdata, 2, relQuantPCR)
geneStabM(relData[,c(3,4)])
exprData <- normPCR(SLqPCRdata, c(3,4))

Example output

      HK1       HK2 
0.2574717 0.2574717 

SLqPCR documentation built on Nov. 8, 2020, 5:12 p.m.