happyplot               package:happy               R Documentation

_P_l_o_t_t_i_n_g _f_u_n_c_t_i_o_n_s _f_o_r _h_a_p_p_y _m_o_d_e_l _f_i_t_s

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

     happyplot() will plot along the genome the log P-value that a QTL
     is not found in a series of marker intervals. It accepts as input
     the results of hfit(), mfit() and mergefit(). mergeplot() is a
     convenience function for calling happlyplot() after a call to
     mergefit(), with several parameters set.

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

      
     happyplot( fit, mode='logP', labels=NULL, xlab='cM', ylab=NULL, main=NULL, t='s', pch=20, ... ) 
     mergeplot( fit, mergedata, mode='logP', xlab='bp', ylab=NULL, main=NULL,  t='p', pch=20, ... ) 

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

     fit: an object returned by a previous call to hfit(), mfit(), or
          mergefit() 

    mode: the mode of the plot - either 'logP', when the negative
          base-10 logarithm of the ANOVA P-value of plotted, or 'SS',
          when the fitting sums-of-squares is plotted

  labels: optional matrix detailing marker labels to be drawn on the
          plot. The labels are written vertically above the plot, with
          vertical lines extending down into the plot area. labels is a
          matrix with two named columns 'marker', containing the marker
          names, and 'POSITION', containing the x-axis positions of the
          markers.

mergedata: (mergeplot() only). an object returned by a previous call to
          mergeprepare(). This is used to construct labels for plotting

    xlab: the x-axis label 

    ylab: the y-axis label 

    main: the titke of the plot 

       t: the type of plot - either 'p', 'l', 's' or 'S', with the same
          meanings as in plot() 

     pch: the plotting character code, with the same meaning as in
          plot() 

     ...: arguments passed down to R plotting functions

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

     A plot to the current graphics device is produced. For happyplot,
     if fit$permdata is not NULL (i.e. hfit() was run using the
     permutation test option) then the plot contains two step
     functions, labelled global.logp and point.logp The global.logp
     plot shows the empirical log-pvalue relative the whole region (ie
     adjusted for the number of markers) while point.logp shows the
     empirical log-pvalue for each interval. If fit$permdata is NULL
     then the plots give the ANOVA logP values. If the model used in 
     hfit() is 'additive' then the logP for the additive mocdel vs the
     null model is plotted; if the model is 'full' then the curves for
     the full, additive and partial F-test logP values are plotted.

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

     Richard Mott

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

     hfit(), mfit(), mergefit()

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

     ## Not run:  h <- happy( 'HS.data', 'HS.alleles' ) 
     ## Not run:  fit <- hfit( h, h$markers, model='full' ) 
     ## Not run:  happyplot( fit ) 

