hierclus          package:Agi4x44PreProcess          R Documentation

_H_i_e_r_a_r_c_h_i_c_a_l _c_l_u_s_t_e_r_i_n_g

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

     Hierarchical cluster of samples using the 'hclust' function

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

     hierclus(object, GErep, methdis, methclu,sel, size)

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

  object: An expression Matrix 

   GErep: Numerical vector that relates each sample with its
          experimental condition 

 methdis: the distance measure to be used. Options are 'euclidean' and
          'pearson'. see 'dist' function  

 methclu: the agglomeration method to be used by the 'hclust' function  

     sel: logical, if 'TRUE' selects the 'size' highest variance genes
          for the plot  

    size: selects the 'size' highest variance genes for the plot if
          'sel=TRUE'  

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

     Pedro Lopez-Romero

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

     hclust,dist

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

     ## Not run: 
             data(dd)
             data(targets)
             GErep=targets$GErep
             selSNR=which(dd$genes$ControlType==0)
             dd.aux=dd[selSNR,]
             index=which(duplicated(dd.aux$genes$ProbeName)==FALSE)
             dd.aux=dd.aux[index,]
             hierclus(dd.aux$G,GErep,methdis="euclidean",
             methclu="complete",sel=FALSE,100)
     ## End(Not run)

