SARP.compo (version 0.1.5)

arbre.Mp: Grouping composants by changes in cut-off separation

Description

These functions construct a tree based on the successive disjunctions between nodes of the graph when increasing the cut-off value.

Usage

arbre.Mp( Mp, en.log = FALSE, reference = NA, complement = FALSE )
# S3 method for Arbre
plot(x, seuil.p = 0.05,
                     xlab = "Composant",
                     ylab = if ( TRUE == en.log ) "-log seuil" else "Seuil",
                     col.seuil = "red"  , lwd.seuil = 1, lty.seuil = 1,
                     horiz = FALSE, center = TRUE, edge.root = TRUE,
                     ...)

Value

The arbre.Mp function returns a dendrogram.

Arguments

Mp

A square, symmetric matrix containing p-values. Element in row \(i\) and line \(j\) should contain the p-value for testing the \(\frac{i}{j}\) ratio. The diagonal is ignored.

en.log

If TRUE, p-values are log-transformed (using decimal logarithm) to construct the tree. It does not change the tree structure, it only helps visualisation of the small p-value part of the tree.

reference

Either NA (the default) or a vector giving the names of reference genes. Corresponding leaves will then be drawn in orange, whereas leaves for genes of interests will be drawn in palegreen (like graphs).

complement

A logical. If TRUE, the tree is built using the complement of the graph, as when using equivalence test to build the graph.

x

The tree to be drawn

seuil.p

Selected cut-off for analysis. Can also be a SARPcompo.H0 object, as returned by choisir.seuil, in which case the bounds of the confidence interval are also drawn, with dashed lines by default.

xlab,ylab

Legends for the axes

col.seuil, lwd.seuil, lty.seuil

Graphical parameters for drawing the analysis cut-off

horiz, center, edge.root

Options from plot.dendrogram with different defaults or needed for complementary plottings. If TRUE, the tree is drawn, respectivally, horizontally instead of vertically, with edges “centered”, and with edge to the root node. See the documentation from plot.dendrogram for details.

...

Additionnal parameters for plot.dendrogram, which is used internally.

Author

Emmanuel Curis ()

Details

By increasing the cut-off from 0 to 1, more and more edges between nodes are removed, and disjoint subgraphs appear. This can be used to build a tree of the composants, with nodes of the tree corresponding to the apparition of a new distinct subgraph. Leafs of the tree are the individual components.

See Also

creer.Mp to create a matrix of p-values for all possible ratios of a compositional vector.

grf.Mp to convert such a matrix to a graph, once a cut-off is selected.

coupures.Mp to obtain the set of p-values corresponding to the nodes of the tree, that is to the apparition of new sets of composants.

plot.dendrogram and as.dendrogram for more details on dendrogram drawing and structure.

Examples

   # load the potery data set
   data( poteries )

   # Compute one-way ANOVA p-values for all ratios in this data set   
   Mp <- creer.Mp( poteries, c( 'Al', 'Na', 'Fe', 'Ca', 'Mg' ),
                   f.p = anva1.fpc, v.X = 'Site' )

   # Build the tree (in log scale, p-values are all < 0.01)
   arbre <- arbre.Mp( Mp, en.log = TRUE )

   # It is a dendrogram as defined in the cluster package
   str( arbre )
   class( arbre )

   # Drawing this tree
   plot( arbre )