badCt {EasyqpcR} | R Documentation

## Evaluation of the qPCR technical replicates

### Description

This function allows you to evaluate your qPCR technical replicates, you only need to define the threshold (according to Hellemans et al. (2007), 0.5 is a good threshold value), the dataset and the number of technical replicates you have done. I recommand you to use the gWidgets package to easily exclude the failed replicates.

### Usage

    badCt(data, r, threshold, na.rm = FALSE)

### Arguments

`data` | data.frame containing row datas (genes in columns, samples in rows, Cq values).
`r` | numeric, number of qPCR replicates.
`threshold` | numeric, the maximal variation between your qPCR replicates.
`na.rm` | a logical value indicating whether NA values should be stripped before the computation proceeds.

### Details

To facilitate the use of the function, I suggest you to use the gWidgets package as described in the vignette.

### Value

This function returns the position (sample position and column position) where the variation between qPCR replicates is superior to the threshold value.

### Author(s)

Sylvain Le pape <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)

    badCt(data=qPCR_run1, r=3, threshold=0.3, na.rm=TRUE)

[Package EasyqpcR version 1.28.0 Index]