hierM               package:maigesPack               R Documentation

_F_u_n_c_t_i_o_n _t_o _d_o _h_i_e_r_a_r_c_h_i_c_a_l _c_l_u_s_t_e_r _a_n_a_l_y_s_i_s

_D_e_s_c_r_i_p_t_i_o_n:

     This is a function to do hierarchical clustering analysis for
     objects of classes 'maiges', 'maigesRaw' and 'maigesANOVA'. Use
     the function 'hierMde' for objects of class 'maigesDEcluster'.

_U_s_a_g_e:

     hierM(data, group=c("C", "R", "B")[1], distance="correlation",
           method="complete", doHeat=TRUE, sLabelID="SAMPLE",
           gLabelID="GeneName", rmGenes=NULL, rmSamples=NULL,
           rmBad=TRUE, geneGrp=NULL, path=NULL, ...)

_A_r_g_u_m_e_n_t_s:

    data: object of class 'maigesRaw', 'maiges', 'maigesANOVA' or
          'maigesDEcluster'.

   group: character string giving the type of grouping: by rows 'R',
          columns 'C' (default) or both 'B'.

distance: char string giving the type of distance to use. Here we use
          the function 'Dist' and the possible values are 'euclidean',
          'maximum', 'manhattan', 'canberra', 'binary', 'pearson',
          'correlation' (default) and 'spearman'.

  method: char string specifying the linkage method for the
          hierarchical cluster. Possible values are 'ward', 'single',
          'complete' (default), 'average', 'mcquitty', 'median' or
          'centroid'

  doHeat: logical indicating to do or not the heatmap. If FALSE, only
          the dendrogram is displayed.

sLabelID: character string specifying the sample label ID to be used to
          label the samples.

gLabelID: character string specifying the gene label ID to be used to
          label the genes.

 rmGenes: char list specifying genes to be removed.

rmSamples: char list specifying samples to be removed.

   rmBad: logical indicating to remove or not bad spots (slot
          'BadSpots' in objects of class 'maiges', 'maigesRaw' or
          'maigesANOVA').

 geneGrp: numerical or character specifying the gene group to be
          clustered. This is given by the columns of the slot
          'GeneGrps' in objects of classes 'maiges', 'maigesRaw' and
          'maigesANOVA'.

    path: numerical or character specifying the gene network to be
          clustered. This is given by the items of the slot 'Paths' in
          objects of classes 'maiges', 'maigesRaw' and 'maigesANOVA'.

     ...: additional parameters for 'heatmap' function.

_D_e_t_a_i_l_s:

     This function implements the hierarchical clustering method for
     objects of microarray data defined in this package. The default
     function for hierarchical clustering is the 'hclust'.

_V_a_l_u_e:

     This function display the heatmaps and don't return any object or
     value.

_A_u_t_h_o_r(_s):

     Gustavo H. Esteves <gesteves@vision.ime.usp.br>

_S_e_e _A_l_s_o:

     'somM' and 'kmeansM' for displaying SOM and k-means clusters,
     respectively.

_E_x_a_m_p_l_e_s:

     ## Loading the dataset
     data(gastro)

     ## Doing a hierarchical cluster using all genes, for maigesRaw class
     hierM(gastro.raw, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
           sLabelID="Sample", gLabelID="Name", doHeat=FALSE)

     ## Doing a hierarchical cluster using all genes, for maigesNorm class
     hierM(gastro.norm, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
           sLabelID="Sample", gLabelID="Name", doHeat=FALSE)

     ## If you want to show the heatmap do
     hierM(gastro.norm, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
           sLabelID="Sample", gLabelID="Name", doHeat=TRUE)

     ## If you want to show the hierarchical branch in both margins do
     hierM(gastro.summ, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
           sLabelID="Sample", gLabelID="Name", doHeat=TRUE, group="B")

     ## If you want to use euclidean distance only into rows (spots or genes)
     hierM(gastro.summ, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
           sLabelID="Sample", gLabelID="Name", doHeat=FALSE, group="R", distance="euclidean")

