HeatmapMethods         package:GeneSelector         R Documentation

_H_e_a_t_m_a_p _o_f _g_e_n_e_s _a_n_d _r_a_n_k_i_n_g _p_r_o_c_e_d_u_r_e_s

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

     Cluster genes and ranking procedures simultanesously  based on a
     data matrix of ranks whose columns correspond to ranking
     procedures and whose rows correspond to genes. The main goal is to
     compare different ranking procedures and to examine whether there
     are big differences among  them. Up to now, the (totally
     unweighted) euclidean metric and complete-linkage clustering is
     used to generate the trees. It should be mentionned that this
     method only fulfills an exploratory task.

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

     HeatmapMethods(Rlist, ind = 1:100)

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

   Rlist: A list of objects of class GeneRanking  or AggregatedRanking.

     ind: A vector of gene indices whose ranks are used to generate the
          heatmap. The number of elements should not be too large (not
          greater than 500) due high time and memory requirements.

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

     A heatmap (plot).

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

     Martin Slawski martin.slawski@campus.lmu.de 
      Anne-Laure Boulesteix <URL: http://www.slcmsr.net/boulesteix>

_R_e_f_e_r_e_n_c_e_s:

     Gentleman, R., Carey, V.J, Huber, W., Irizarry, R.A,  Dudoit, S.
     (editors), 2005.
      Bioinformatics and Computational Biology Solutions Using R and
     Bioconductor chapter 10, Visualizing Data. _Springer, N.Y._

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

     ## Load toy gene expression data
     data(toydata)
     ### class labels
     yy <- toydata[1,]
     ### gene expression
     xx <- toydata[-1,]
     ### Get Rankings from five different statistics
     ordinaryT <- RankingTstat(xx, yy, type="unpaired")
     baldilongT <- RankingBaldiLong(xx, yy, type="unpaired")
     samT <- RankingSam(xx, yy, type="unpaired")
     wilc <- RankingWilcoxon(xx, yy, type="unpaired")
     wilcebam <- RankingWilcEbam(xx, yy, type="unpaired")
     ### form a list
     LL <- list(ordinaryT, baldilongT, samT, wilc, wilcebam)
     ### plot the heatmap
     HeatmapMethods(LL, ind=1:100)

