Description Usage Arguments Value Author(s) Examples

Plot DiffCorr group

1 2 3 |

`data` |
a data matrix or data frame |

`groups1` |
a vector of row group membership as produced by cutree under condition 1 |

`groups2` |
a vector of row group membership as produced by cutree under condition 2 |

`group1.no` |
the group number to be plotted (condition 1) |

`group2.no` |
the group number to be plotted (condition 2) |

`g1` |
a vector describing the columns of the data belonging to condition 1 |

`g2` |
a vector describing the columns of the data belonging to condition 2 |

`g1.order` |
whether or not to order the columns of the data matrix for condition 1. If "average", then the columns are ordered by the average expression value. If the name of a gene (row), then the columns are orderd according to the expression levels of that gene. If NULL, columns remain in their original order. |

`g2.order` |
See g1.order |

`title1` |
A title for the left hand graph |

`title2` |
A title for the right hand graph |

`...` |
other parameters to be passed to this function |

a graph

Atsushi Fukushima

1 2 3 4 5 6 7 8 9 10 | ```
library(pcaMethods)
data(golub, package = "multtest")
hc.mol1 <- cluster.molecule(golub[, 1:27], "pearson", "average")
hc.mol2 <- cluster.molecule(golub[, 28:38], "pearson", "average")
g1 <- cutree(hc.mol1, h=0.4)
g2 <- cutree(hc.mol2, h=0.4)
##
plotDiffCorrGroup(golub, g1, g2, 21, 24, 1:27, 28:38,
scale.center=TRUE, scale.scale=TRUE,
ylim=c(-5,5))
``` |

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