plot.confband.lines           package:sma           R Documentation

_A_d_d_i_n_g _L_i_n_e_s _S_a_t_i_s_f_y_i_n_g _a _C_o_n_f_i_d_e_n_c_e _C_r_i_t_e_r_i_o_n _t_o _t_h_e _C_u_r_r_e_n_t _M
_v_s _A _P_l_o_t

_D_e_s_c_r_i_p_t_i_o_n:

     This function adds 2 lines outlining the pointwise (intensity
     dependent) confidence band on the M vs A plot.  The lines are
     drawn such that a prespecified proportion of points are outside
     the 2 confidence curves. The type of line may be specified as well
     as other parameters.

_U_s_a_g_e:

     plot.confband.lines(x, M, crit1=0.025, crit2=crit1, nclass=10, ...)

_A_r_g_u_m_e_n_t_s:

       x: a vector giving the x-coordinates of the points in the
          scatter plot. In the microarray context, this could be a
          vector of average log intensities, ie A

       M: a vector giving the y-coordinates of the points in the
          scatter plot. In the microarray context, this could be a
          vector of log intensity ratios.

   crit1: The proportion of points less than the lower confidence
          curve.  This takes a decimal value between 0 and 1. 

   crit2: The proportion of points greater than the upper confidence
          curve.  By default, this has the same value as "crit1".

  nclass: A single number giving the approximate number of intensity
          depedent groups to consider.

     ...: graphical parameters may also be supplied as arguments to the
          function (see  'par').

_V_a_l_u_e:

     Lines are added to the current plot.

_N_o_t_e:

     An M vs A plot must be constructed *prior* to the execution of
     this function.

_S_e_e _A_l_s_o:

     'plot.mva', 'stat.ma', 'lines', 'matlines', 'plot.confband.text',
     'plot.confband.points' .

_E_x_a_m_p_l_e_s:

     data(MouseArray)
     ## mouse.setup <- init.grid
     ## mouse.data <- init.data

     ## To display an M vs A plot of the data 
     plot.mva(mouse.data, mouse.setup) 

     ## Calculate M and A values 
     mouse.lratio <- stat.ma(mouse.data, mouse.setup)

     ## To add default upper and lower confidence curves line to the M vs A plot
     plot.confband.lines(mouse.lratio$A, mouse.lratio$M) 

