plotFeature               package:HELP               R Documentation

_P_l_o_t _f_e_a_t_u_r_e _v_e_r_s_u_s _t_w_o-_c_o_l_o_r _i_n_t_e_n_s_i_t_y

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

     Graphical display of featureData (ex: fragment size) versus
     two-color signal intensity data

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

     plotFeature(x, y, ...)

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

       x: matrix of numerical data to be plotted, with two columns (one
          for each signal channel). 'x' can also be of class
          '"ExpressionSet"'. 

       y: an additional vector of numerical data to be used for
          feature. If 'y' is missing, the function will attempt to fill
          a value from 'featureData' in 'x'. 

     ...: Arguments to be passed to methods (see
          'plotFeature-methods'):

          '_e_l_e_m_e_n_t._x' which element of 'AssayData' to use (for signal
               channel 1) for a given 'ExpressionSet' input (default is
               '"exprs"') 

          '_e_l_e_m_e_n_t._y' which element of 'AssayData' to use (for signal
               channel 2) for a given 'ExpressionSet' input (default is
               '"exprs2"') 

          '_s_a_m_p_l_e' which element of 'sampleNames' to use as data
               (default is 1). Can be a character matching a sample
               name or simply an integer indicating which sample to
               choose. 

          '_f_e_a_t_u_r_e' which element of 'featureData' to use as plotting
               feature (default is 1). Can be a character matching
               'varLabel' or simply an integer indicating which feature
               to choose. 

          '_f_e_a_t_u_r_e._r_a_n_d_o_m' which element of 'featureData' to use to
               identify random probes (default is '"TYPE"'). Can be a
               character matching 'varLabel' or simply an integer
               indicating which feature to choose. 

          '_w_h_i_c_h._r_a_n_d_o_m' an integer vector specifying which rows of
               data correspond to random probes. if 'NULL' (default),
               the function will attempt to identify random probes
               using 'featureData'. 

          '_r_a_n_d_o_m._f_l_a_g' a character specifying the label for random
               probes in 'feature.random' from 'featureData'. Default
               is '"RAND"'. 

          '_n_a._r_m' logical; if 'TRUE' (default), missing values are
               removed from 'x'. If 'FALSE' any missing values cause an
               error.

          '_l_i_m_i_t' numerical input specifying the maximum number of
               points to plot (default is 10,000). if 'NULL', all
               points will be used.

          '_c_u_t_o_f_f' a numerical input specifying the value below which
               signal intensities from channel 1 can be considered
               "failed" probes. If 'NULL' (default), the function will
               attempt to calculate a cutoff from random probe
               information.

          '_c_u_t_o_f_f_2' a numerical input specifying the value below which
               signal intensities from channel 2 can be considered
               "failed" probes. If 'NULL' (default), the function will
               attempt to calculate a cutoff from random probe
               information.

          '_m_a_i_n' an overall title for the plot: see 'title'. 

          '_x_l_a_b' a title for the x axis (default is '"Fragment size
               (bp)"'): see 'title'. 

          '_y_l_a_b' a title for the y axis for signal channel 1 (default
               is '"log(MspI)"'): see 'title'. 

          '_y_l_a_b_2' a title for the y axis for signal channel 2 (default
               is '"log(HpaII)"'): see 'title'. 

          '_c_e_x' numerical value (default is 0.2) giving the amount by
               which plotting text and symbols should be scaled
               relative to the default.  

          '...' other arguments to be passed to 'plot'. See 'plot'.  

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

     Reid F. Thompson (rthompso@aecom.yu.edu)

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

     'plotFeature-methods'

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

     #demo(pipeline,package="HELP")

     msp1 <- sample(8000:16000/1000, size=1000)
     msp1 <- msp1[order(msp1)]
     hpa2 <- sample(8000:16000/1000, size=1000)
     hpa2 <- hpa2[order(hpa2)]
     size <- sample((1:1000)*1.8+200, size=1000)
     rand <- which.min(abs(msp1-quantile(msp1, 0.25)))
     plotFeature(cbind(msp1, hpa2), size, which.random=(rand-20):(rand+20), main="Random")

     #rm(msp1, hpa2, size, rand)

