overview                package:made4                R Documentation

_D_r_a_w _b_o_x_p_l_o_t, _h_i_s_t_o_g_r_a_m _a_n_d _h_i_e_r_a_r_c_h_i_c_a_l _t_r_e_e _o_f _g_e_n_e _e_x_p_r_e_s_s_i_o_n _d_a_t_a

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

     Very simple wrapper function that draws a boxplot, histogram and
     hierarchical tree of expression  data

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

     overview(dataset, labels = NULL, title = "", classvec = NULL, hc = TRUE, boxplot = TRUE, hist = TRUE, returnTree=FALSE) 

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

 dataset: a 'matrix', 'data.frame',  'exprSet' or 'marrayRaw'.   If the
          input is gene expression data in a 'matrix' or 'data.frame'.
          The  rows and columns are expected to contain the variables
          (genes) and cases (array samples)  respectively.

  labels: Vector, labels to be placed on samples in plots. Default is
          rownames(dataset)

   title: Character, label to be placed on plots. Default is NULL

classvec: A 'factor' or 'vector' which describes the classes in columns
          of the 'dataset'.  Default is NULL. If included columns
          (array samples) on the dendrogram will be coloured by class.

      hc: Logical. Draw dendrogram of hierarchical cluster analysis of
          cases. Default is TRUE

 boxplot: Logical. Draw boxplot. Default is TRUE

    hist: Logical. Draw histogram. Default is TRUE

returnTree: Logical. Return the hieracrhical cluster analysis results.
          Default is FALSE

     ...: further arguments passed to or from other methods 

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

     The hierarchical plot is produced using average linkage cluster
     analysis with Eisen's  correlation metric.

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

_N_o_t_e:

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

     Aedin Culhane

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

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

     See also as 'boxplot', 'hclust',  'hist'

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

       data(khan)

       logkhan<-log2(khan$train)
       print(class(logkhan))
       overview(logkhan, title="Subset of Khan Training data")
       overview(logkhan, classvec=khan$train.classes, labels=khan$train.classes)

