somMde              package:maigesPack              R Documentation

_F_u_n_c_t_i_o_n _t_o _d_o _S_O_M _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 SOM (Self Organising Maps) clustering
     analysis for objects of classes 'maigesDEcluster'.

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

     somMde(data, group=c("C", "R")[1], distance="correlation",
            method="complete", sampleT=NULL, doHier=FALSE, sLabelID="SAMPLE",
            gLabelID="GeneName", idxTest=1, adjP="none", nDEgenes=0.05, ...)

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

    data: object of class 'maigesDEcluster'.

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

distance: char string giving the type of distance to use. Only two
          options are available here: 'euclidean' and 'correlation'
          (default).

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

 sampleT: list with 2 vectors. The first one specify the first letter
          of different sample types to be coloured by distinct colours,
          that are given in the second vector. If NULL (default) no
          colour is used.

  doHier: logical indicating if you want to do the hierarchical branch
          in the opposite dimension of clustering. Defaults to FALSE.

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.

 idxTest: numerical index of the test to be used to sort the genes when
          clustering objects of class 'maigesDEcluster'.

    adjP: string specifying the method of p-value adjustment. May be
          'none', 'Bonferroni', 'Holm', 'Hochberg', 'SidakSS',
          'SidakSD', 'BH', 'BY'.

nDEgenes: number of DE genes to be selected. If a real number in (0,1)
          all genes with p.value <= 'nDEgenes' will be used. If an
          integer, the 'nDEgenes' genes with smaller p-values will be
          used.

     ...: additional parameters for 'som' function.

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

     This function implements the SOM clustering method for objects
     resulted from differential expression analysis. The method uses
     the function 'som' from package _som_. For the adjustment of
     p-values in the selection of genes differentially expressed, we
     use the function 'mt.rawp2adjp' from package _multtest_.

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

     This function display the heatmaps and return invisibly an object
     of class 'som' resulted from the function 'som'.

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

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

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

     'som' from package _som_. 'kmeansM' and 'hierM' for displaying
     k-means and hierarchical clusters, respectively.

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

     ## Loading the dataset
     data(gastro)

     ## Doing bootstrap from t statistic test fot 'Type' sample label, k=1000
     ## specifies one thousand bootstraps
     gastro.ttest = deGenes2by2Ttest(gastro.summ, sLabelID="Type")

     ## SOM cluster with 2 groups adjusting p-values by FDR, and showing all genes
     ## with p-value < 0.05
     somMde(gastro.ttest, sLabelID="Type", adjP="BH", nDEgenes=0.05,
            xdim=2, ydim=1, topol="rect")

     ## SOM cluster with 4 groups adjusting p-values by FDR, and showing all genes
     ## with p-value < 0.05
     somMde(gastro.ttest, sLabelID="Type", adjP="BH", nDEgenes=0.05,
            xdim=2, ydim=2, topol="rect")

