ord                  package:made4                  R Documentation

_O_r_d_i_n_a_t_i_o_n

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

     Run principal component analysis, correspondence analysis or
     non-symmetric correspondence analysis  on gene expression data

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

     ord(dataset, type="coa", classvec=NULL, ...)
     plot.ord(x, axes1=1, axes2=2, arraycol=NULL, genecol="gray25", nlab=10, genelabels= NULL, classvec=NULL, ...)

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

 dataset: Training 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. 

classvec: A 'factor' or 'vector' which describes the classes in the
          training dataset

    type: Character, "coa", "pca" or "nsc" indicating which data
          transformation is required. The default value is type="coa"

       x: An object of class 'ord'.  The output from 'ord'. It contains
          the projection coordinates from 'ord',  the $co or $li
          coordinates to be plotted

arraycol, genecol: Character, colour of points on plot. If arraycol is
          NULL,  arraycol will obtain a set of contrasting colours
          using 'getcol', for each classes  of cases (microarray
          samples) on the array (case) plot.  genecol is the colour of
          the  points for each variable (genes) on gene plot

    nlab: Numeric. An integer indicating the number of variables
          (genes) at the end of axes to be labelled, on the gene plot.

   axes1: Integer, the column number for the x-axis. The default is 1.

   axes2: Integer, the column number for the y-axis, The default is 2.

genelabels: A vector of variables labels, if 'genelabels'=NULL the
          row.names  of input matrix 'dataset' will be used

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

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

     'ord' calls either 'dudi.pca', 'dudi.coa' or 'dudi.nsc' on the
     input dataset.  The input format of the dataset  is verified using
     'array2ade4'. 

     If the user defines microarray sample groupings, these are colours
     on plots produced by 'plot.ord'. 

     *Plotting and visualising bga results:*

     _2D plots:_  's.var' and 's.groups' to draw an xy plot of cases
     ($ls).  's.var' and 's.groups' are modifications of the ADE4
     graphing functions  's.label' and 's.class'.   'plotgenes', is
     used to draw an xy plot of the variables (genes). 

     _3D plots:_ 3D graphs can be generated using 'do3D' and 'html3D'. 
     'html3D' produces a web page in which a 3D plot can be
     interactively rotated, zoomed, and in which classes or groups of
     cases can be easily highlighted. 

     _1D plots, show one axis only:_ 1D graphs can be plotted using 
     'graph1D'.  'graph1D'  can be used to plot either cases
     (microarrays) or variables (genes) and only requires a vector of
     coordinates ($li, $co)

     *Analysis of the distribution of variance among axes:*

     The number of axes or  principal components from a 'ord' will
     equal 'nrow' the number of rows, or the  'ncol', number of columns
     of the dataset (whichever is less).

     The distribution of variance among axes is described in the
     eigenvalues ($eig) of the 'ord' analysis.  These can be visualised
     using a scree plot, using 'scatterutil.eigen' as it done in
     'plot.ord'.   It is also useful to visualise the principal
     components from a using a 'ord' or principal components analysis 
     'dudi.pca', or correspondence analysis 'dudi.coa' using a heatmap.
     In MADE4 the function 'heatplot' will plot a heatmap with nicer
     default colours.

     *Extracting list of top variables (genes):*

     Use 'topgenes'  to get list of variables or cases at the ends of
     axes.  It will return a list of the top n variables (by default
     n=5) at the positive, negative or both ends of an axes.  
     'sumstats' can be used to return the angle (slope) and distance
     from the origin of a list of coordinates.

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

     A list with a class 'ord' containing:

     ord: Results of initial ordination. A list of class "dudi" (see
          'dudi' )

     fac: The input classvec, the 'factor' or 'vector' which described
          the classes in the input dataset. Can be null.

_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  'dudi.pca', 'dudi.coa' or 'dudi.nsc', 'bga',

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

     data(khan)

     if (require(ade4, quiet = TRUE)) {
       khan.coa<-ord(khan$train, classvec=khan$train.classes, type="coa")  
       }

     khan.coa
     plot(khan.coa, genelabels=khan$annotation$Symbol)

     # Provide a view of the first 5 principal components (axes) of the correspondence analysis
     heatplot(khan.coa$ord$li[,1:5], dend=FALSE,lowcol="blue")

