heatplot                package:made4                R Documentation

_D_r_a_w_s _h_e_a_t_m_a_p _w_i_t_h _d_e_n_d_r_o_g_r_a_m_s.

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

     'heatplot' calls 'heatmap.2' using a red-green colour scheme by
     default.  It also draws dendrograms of the cases and variables
     using correlation similarity metric and average linkage clustering
     as described by Eisen. 'heatplot' is useful for a quick overview
     or exploratory analysis of data

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

     heatplot(dataset, dend = c("both", "row", "column", "none"),  cols.default = TRUE, lowcol = "green", highcol = "red", scale="row",  classvec=NULL, classvec2=NULL,  ...)

_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. 

    dend: A character indicating whether dendrograms should be drawn
          for both rows and columms "both", just rows "row" or column
          "column" or no dendrogram "none". Default is both.

cols.default: Logical. Default is TRUE. Use blue-brown color scheme

lowcol, highcol: Character indicating colours to be used for down and
          upregulated genes when drawing heatmap if the default colors
          are not used, that is cols.default = FALSE.

   scale: Default is row. Scale and center either  "none","row", or
          "column")

classvec: A 'factor' or 'vector' which describes the classes in columns
          or rows of the 'dataset'.  Default is NULL. If included, a
          color bar including the class of each column (array sample)
          or row (gene) will be drawn. It will automatically add to
          either the columns or row, depending if the
          length(as.character(classvec)) ==nrow(dataset) or
          ncol(dataset)

classvec2: A 'factor' or 'vector' which describes the classes in
          columns or rows of the 'dataset'.  Default is NULL. If
          included, a color bar including the class of each column
          (array sample) or row (gene) will be drawn. It will
          automatically add to either the columns or row, depending if
          the length(as.character(classvec)) ==nrow(dataset) or
          ncol(dataset)

     ...: 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 a correlation metric distance.  'heatplot' calls
     'heatmap.2' in the R package 'gplots'.

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

     Plots a heatmap with dendrogram of hierarchical cluster analysis

_N_o_t_e:

     Because Eisen et al., 1998 use green-red colours for the heatmap
     'heatplot'  uses these by default however a blue-red or
     yellow-blue are easily obtained by  changing lowcol and highcol

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

     Aedin Culhane

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

     Eisen MB, Spellman PT, Brown PO and Botstein D. (1998). Cluster
     Analysis and Display of  Genome-Wide Expression Patterns. Proc
     Natl Acad Sci USA 95, 14863-8.

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

     See also as 'hclust',  'heatmap' and 'dendrogram'

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

     data(khan)

     heatplot(khan$train[1:30,], cols.default=FALSE, lowcol="white", highcol="red")
     heatplot(khan$train[1:26,], labCol = c(64:1), labRow=LETTERS[1:26])

     heatplot(khan$train[1:26,], classvec=khan$train.classes)

     if (require(ade4, quiet = TRUE)) {
     res<-ord(khan$train, ord.nf=5)  # save 5 components from correspondence analysis
     khan.coa = res$ord
     }

     # Provides a view of the components of the Correspondence analysis (gene projection) in the lines (row)
     heatplot(khan.coa$li)    # first 5 components
     heatplot(khan.coa$li, margins=c(4,20))  # Change the margin size. The default is c(5,5)

       
     # Sample projection (columns)
     # See that the difference between tissues and cell line samples are defined in the first axis.

     heatplot(khan.coa$co,classvec2=khan$train.classes, cols.default=FALSE, lowcol="blue", dend="row", scale="none")

