imageLimma {genArise} | R Documentation |

## Image Plot of Microarray

### Description

Plot an image of colours representing the log intensity ratio for each
spot on the array. This function can be used to explore whether there
are any spatial effects in the data.

### Usage

imageLimma(z, row, column, meta.row, meta.column,
low = NULL, high = NULL)

### Arguments

`z` |
numeric vector or array. This vector can contain any spot
statistics, such as log intensity ratios, spot sizes or
shapes, or t-statistics. Missing values are allowed and will
result in blank spots on the image |

`row` |
rows in the microarray |

`column` |
columns in the microarray |

`meta.row` |
metarows in the microarray |

`meta.column` |
metacolumns in the microarray |

`low` |
color associated with low values of 'z'. May be specified as
a character string such as '"green"', '"white"' etc, or as a
rgb vector in which 'c(1,0,0)' is red, 'c(0,1,0)' is green
and 'c(0,0,1)' is blue. The default value is '"green"' if
'zerocenter=T' or '"white"' if 'zerocenter=F'. |

`high` |
color associated with high values of 'z'. The default value
is '"red"' if 'zerocenter=T' or '"blue"' if 'zerocenter=F'. |

### Note

This function is based in the imageplot function from limma package.

### References

Gordon K. Smyth (2004) "Linear Models and Empirical Bayes Methods for
Assessing Differential Expression in Microarray Experiments",
Statistical Applications in Genetics and Molecular Biology: Vol. 3:
No. 1, Article 3.
http://www.bepress.com/sagmb/vol3/iss1/art3

### Examples

data(Simon)
spot.data <- attr(Simon, "spotData")
M <- log(spot.data$Cy3, 2) - log(spot.data$Cy5, 2)
imageLimma(z = M, row = 23, column = 24, meta.row = 2, meta.column = 2,
low = NULL, high = NULL)

[Package

*genArise* version 1.0.0

Index]