Description Usage Arguments Value Examples

View source: R/compareModules.R

This takes a correlation matrix or 3D landmark array, a model definition, and then two module numbers or names to compare. It plots (if plot = TRUE) a figure of three boxplots - the first two are the correltions within each of the two modules, and the third is the between-module correlations. These boxes are coloured such that matching colours are not significantly different according to a Tukey HSD test. The results of the anova and tukey HSD test are also returned.

1 | ```
compareModules(corr, model, test_modules, plot = TRUE)
``` |

`corr` |
A correlation matrix or a 3D array of landmarks. If 3D then a correlation matrix is calculated with dotcorr |

`model` |
Either a vector of numbers describing a model of modules, or a 2 column dataframe with the first bein landmark names and the second being the module definitions. |

`test_modules` |
A vector of two module numbers to compare, or if the modules are named, the names of those two modules. |

`plot` |
Logical - if TRUE the plot is drawn. |

A list with two elements - the first is the result of an ANOVA compaing the mean correlations within- and between-modules, and the second is the results of a TukeyHSD test on that ANOVA. If plot = TRUE a plot showing these results is called.

1 2 3 4 5 6 7 8 9 | ```
data(macacaCorrel)
data(macacaModels)
# Pick a model to draw modules from - as a vector.
model <- macacaModels$Goswami
compareModules(corr = macacaCorrel, model = model, test_modules = c(2, 5))
# Or as a 2 column dataframe...
model <- macacaModels[ , c(1, 4)]
compareModules(corr = macacaCorrel, model = model, test_modules = c(2, 5))
``` |

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