plot                 package:KCsmart                 R Documentation

_P_l_o_t _a _s_a_m_p_l_e _p_o_i_n_t _m_a_t_r_i_x

_D_e_s_c_r_i_p_t_i_o_n:

     Plot the sample point matrix or parts of it

_U_s_a_g_e:

     plot(x,y, ...)
     ## S4 method for signature 'scaleSpace, missing':
     plot(x, y, spm, type='b', ...)
     ## S4 method for signature 'samplePointMatrix, missing':
     plot(x, y, type="b", sigLevels=NULL, chromosomes=NULL, colinAxis=NULL, fillColor=NULL, maploc=NULL, interpolation=1, ...)

_A_r_g_u_m_e_n_t_s:

       x: either an object of class samplePointMatrix or scaleSpace

       y: object of class missing

    type: Determines which data is plotted. 'g' for gains only, 'l' for
          losses only and 'b' and '1' for both in one plot device

     spm: add stuff here

sigLevels: If given, the cutoffs will be drawn as lines in the plots.
          Optional 

chromosomes: Takes a vector of chromosomes to be plotted. Defaults to
          all chromosomes. 

colinAxis: Allows you to override default behaviour of axis labeling.
          Choose False for genomic position labeling for each
          individual chromosome, True for colinear labeling.

fillColor: Allows you to choose the colors used to fill the significant
          areas under the curve. Takes a list with the 'pos' element
          giving the color for the gains and the 'neg' element the
          color for the losses. 

  maploc: Currently not in use

interpolation: Determines which points from the sample point matrix
          will actually be plotted. If the value of 'interpolation' is
          n, then every n-th point will be plotted. The default value
          of 1 will results in all points being plotted. This can be
          useful when a high density sample point matrix results in big
          file size when exporting the image (especially to pdf or eps
          format).

     ...: Any other parameters you would like to pass to 'plot'. See
          'par' for more details.

_V_a_l_u_e:

     Plots the sample point matrix. The gains and the losses are
     plotted separately. The KC normalized score is plotted on the
     y-axis, the genomic position on the x-axis. If centromeres are
     present these are represented by dotted, lightblue lines. Setting
     type to 'b' or to '1' will both make the plot appear in one plot
     device, '1' will plot the gains and the losses in one plot, 'b'
     will plot the gains and losses separately. The function 'idPoints'
     can be used to identify points in the sample point matrix plot.
     See the corresponding documentation for details.

_A_u_t_h_o_r(_s):

     Jorma de Ronde

_S_e_e _A_l_s_o:

     'calcSpm', 'plotScaleSpace', 'idPoints'

_E_x_a_m_p_l_e_s:

     data(hsSampleData)
     data(hsMirrorLocs)

     spm1mb <- calcSpm(hsSampleData, hsMirrorLocs)

     plot(spm1mb)
     plot(spm1mb, interpolation=10)
     plot(spm1mb, chromosomes=c(1,4,'X'))

     siglevel1mb <- findSigLevelTrad(hsSampleData, spm1mb, n=3)
     plot(spm1mb, chromosomes=c(1,4,'X'), sigLevels=siglevel1mb)
     plot(spm1mb, chromosomes=c(1,4,'X'), sigLevels=siglevel1mb, fillColor=list(pos='darkred',neg='darkgreen'))

