clusterVisualNone-class      package:goCluster      R Documentation

_C_l_a_s_s "_c_l_u_s_t_e_r_V_i_s_u_a_l_N_o_n_e", _a _p_l_a_c_e_h_o_l_d_e_r _f_o_r _t_h_e _g_o_C_l_u_s_t_e_r 
_v_i_s_u_a_l_i_z_a_t_i_o_n _m_e_t_h_o_d_s

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

     The class can be used to avoid specifying a visualization method
     when performing an analysis with 'goCluster'.

_S_l_o_t_s:

     All slots are described in the documentation for the
     'clusterModule-class'.

_E_x_t_e_n_d_s:

     Class '"clusterVisual"', directly. Class '"clusterModule"', by
     class '"clusterVisual"'.

_M_e_t_h_o_d_s:

     _c_o_n_f_i_g 'signature(object = "clusterVisualNone")': The  class has
          no parameters. This method does not result in any action.

     _e_x_e_c_u_t_e 'signature(object = "clusterVisualNone")': The  class has
          no executable function defined and will do nothing. 

     _s_e_t_u_p 'signature(object = "clusterVisualNone")': The  class has no
          parameters. This method returns an empty list. 

     _s_e_t_u_p<- 'signature(object = "clusterVisualNone")': The  class has
          no parameters. This method does not result in any action. 

     _r_e_s_e_t 'signature(object = "clusterVisualNone")': resets the
          results of this class so that the analysis can be run again. 

     _d_i_s_p_l_a_y 'signature(object = "clusterVisualNone")': generates the
          actual graphic for this object. 

     _p_r_i_n_t 'signature(x = "clusterVisualNone")': prints generic
          information about the object. 

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

     Gunnar Wrobel, <URL: work@gunnarwrobel.de>, <URL:
     http://www.gunnarwrobel.de>.

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

     'goCluster-class', 'clusterModule-class', 'clusterVisual-class'

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

     set.seed(1000)

     data(benomylsetupsmall)

     a <- new("goCluster")

     ## This will result in an object without visualization
     execute(a) <- benomylsetupsmall

     ## We can choose and add the visualization method afterwards

     ## Create the visualization method
     b <- new("clusterVisualHeatmap")

     ## Assign the new method to the old goCluster object
     a@visu <- b

     ## Prepare the visualization
     a@visu <- execute(a@visu, a)

     if(interactive()){
     ## This example can only be run in an interactive mode

     ## This plot shows only four genes since the loaded dataset
     ## has been reduced to only 100 genes. Try the same with
     ## the full dataset
     display(a, selection = "GO:0003735")
     }

