plotCtCor {HTqPCR} | R Documentation

## Correlation between Ct values from qPCR data

### Description

Function for plotting the correlation based on Ct values between samples containing high-throughput qPCR data.

### Usage

    plotCtCor(q, col, col.range = c(0, 1), main, mar, ...)

### Arguments

`q` | object of class qPCRset.

`col` | vector of colours to use, defaults to a spectrum from red to blue/purple.
`col.range` | vector, the range of colours to use.
`main` | character string, plot title.
`mar` | vector, the size of the borrom and right hand side margins.
`...` | any other arguments will be passed to the `heatmap.2` function.

### Details

This function may be used to cluster the samples based on Ct values and present the result in a heatmap. Per default the colours are a rainbow scale from 0 to 1.

The correlation is calculated as 1 - the 'Pearson' method. Prior to version 1.9.1 the value plotted was the correlation directly, rather than 1-correlation.

A standard heatmap is drawn, but this can be modified extensively using the arguments available in the `heatmap.2` function.

### Value

A plot is created on the current graphics device.

### Author(s)

Heidi Dvinge

### See Also

`heatmap.2`

### Examples

    data(qPCRraw)
    plotCtCor(qPCRraw)
    plotCtCor(qPCRraw, col.range=c(0,0.6))

[Package HTqPCR version 1.36.0 Index]