calData {EasyqpcR} | R Documentation

## Calculation of calibration factors

### 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) <sylvain.le.pape@univ-poitiers.fr>

### 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)

[Package EasyqpcR version 1.28.0 Index]