calData: Calculation of calibration factors

In slepape/EasyqpcR: EasyqpcR for low-throughput real-time quantitative PCR data analysis

Description

This function determines the calibration factors (CF) using the method described in Hellemans et al. (2007).

Usage

calData(data)

Arguments

data	data.frame containing the NRQs of your calibrator(s) for each gene obtained by the nrmData function of this package.

Details

This function is necessary for comparing different quantitative real-time PCR runs to reduce the inter-run variability (Hellemans et al. (2007)). Then, the results obtained have to be included in an R object and then be inputed in the nrmData function (see the vignette for more informations).

Value

This function returns the calibration factor associated to each gene for the whole runs.

Author(s)

Sylvain Le Pape (IRTOMIT-INSERM U1082) <[e-mail]>

References

Jan Hellemans, Geert Mortier, Anne De Paepe, Frank Speleman and Jo Vandesompele. qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data. Genome Biology 2007, 8:R19 (doi:10.1186/gb-2007-8-2-r19). <url:http://genomebiology.com/2007/8/2/R19>

Examples

data(qPCR_run1,qPCR_run2,qPCR_run3)

nrmData(data = qPCR_run1 , r=3, E=c(2, 2, 2, 2), 
	      Eerror=c(0.02, 0.02, 0.02, 0.02), nSpl=5, 
	      nbRef=2, Refposcol=1:2, nCTL=2, 
	      CF=c(1, 1, 1, 1), CalPos=5, trace=TRUE, geo=TRUE, na.rm=TRUE)

nrmData(data = qPCR_run2 , r=3, E=c(2, 2, 2, 2), 
	      Eerror=c(0.02, 0.02, 0.02, 0.02), nSpl=5, 
	      nbRef=2, Refposcol=1:2, nCTL=2, 
	      CF=c(1, 1, 1, 1), CalPos=5, trace=TRUE, geo=TRUE, na.rm=TRUE)

nrmData(data = qPCR_run3 , r=3, E=c(2, 2, 2, 2), 
	      Eerror=c(0.02, 0.02, 0.02, 0.02), nSpl=5, 
	      nbRef=2, Refposcol=1:2, nCTL=2, 
	      CF=c(1, 1, 1, 1), CalPos=5, trace=TRUE, geo=TRUE, na.rm=TRUE)


## Isolate the calibrator NRQ values of the first biological replicate

a <- nrmData(data = qPCR_run1 , r=3, E=c(2, 2, 2, 2), 
	      Eerror=c(0.02, 0.02, 0.02, 0.02), nSpl=5, 
	      nbRef=2, Refposcol=1:2, nCTL=2, 
	      CF=c(1, 1, 1, 1), CalPos=5, trace=TRUE, geo=TRUE, na.rm=TRUE)[[3]] 

## Isolate the calibrator NRQ values of the first biological replicate

b <- nrmData(data = qPCR_run2 , r=3, E=c(2, 2, 2, 2), 
	      Eerror=c(0.02, 0.02, 0.02, 0.02), nSpl=5, 
	      nbRef=2, Refposcol=1:2, nCTL=2, 
	      CF=c(1, 1, 1, 1), CalPos=5, trace=TRUE, geo=TRUE, na.rm=TRUE)[[3]]
 
## Isolate the calibrator NRQ values of the first biological replicate

c <- nrmData(data = qPCR_run3 , r=3, E=c(2, 2, 2, 2), 
	      Eerror=c(0.02, 0.02, 0.02, 0.02), nSpl=5, 
	      nbRef=2, Refposcol=1:2, nCTL=2, 
	      CF=c(1, 1, 1, 1), CalPos=5, trace=TRUE, geo=TRUE, na.rm=TRUE)[[3]]

## Regrouping the calibrator NRQ values of all the biological replicates

d <- rbind(a, b, c) 

## Calibration factor calculation

e <- calData(d) 

slepape/EasyqpcR documentation built on May 31, 2019, 12:13 p.m.