report.plot              package:MANOR              R Documentation

_A_r_r_a_y _i_m_a_g_e _a_n_d _a _g_e_n_o_m_i_c _r_e_p_r_e_s_e_n_t_a_t_i_o_n _o_f _a _n_o_r_m_a_l_i_z_e_d _a_r_r_a_y_C_G_H

_D_e_s_c_r_i_p_t_i_o_n:

     Displays an array image and a genomic representation of a
     normalized arrayCGH.

_U_s_a_g_e:

     ## S3 method for class 'arrayCGH':
     report.plot(arrayCGH, x="PosOrder", y=c("LogRatioNorm",
       "LogRatio"), chrLim=NULL, layout=TRUE, main=NULL, zlim=NULL, ...)
     ## Default S3 method:
     report.plot(spot.data, clone.data, design, x="PosOrder",
       y=c("LogRatioNorm", "LogRatio"), chrLim=NULL, layout=TRUE, main=NULL,
       zlim=NULL, ...) 

_A_r_g_u_m_e_n_t_s:

arrayCGH: an object of type 'arrayCGH'.

spot.data: data.frame with spot-level information to be passed to
          arrayPlot.

clone.data: data.frame with clone-level information to be passed to
          genome.plot.

  design: vector of length 4 with array design: number of blocks per
          column and per row, number of columns and rows per block.

       x: a variable name from arrayCGH$cloneValues giving the order
          position of the clones along the genome.

       y: a vector of one or two variable names to be plotted on the
          array and along the genome. The first one is taken from
          'arrayCGH\$arrayValues' and is plotted on the array; the
          second one (or the first one if only one name was provided)
          is taken from 'arrayCGH\$cloneValues' and is plotted along
          the genome.

  chrLim: an optional variable name from arrayCGH$cloneValues giving
          the limits of each chromosome.

  layout: if 'TRUE', plot layout is set to a 1*2 matrix with relative
          column widths 1 and 4.

    main: title for the genomic profile.

    zlim: numeric vector of length 2 to be passed to 'arrayPlot':
          minimum and maximum signal values for array image display.

     ...: further arguments to be passed to 'genome.plot'.

_D_e_t_a_i_l_s:

     This function successively calls 'arrayPlot' and 'genome.plot'.

_N_o_t_e:

     People interested in tools for array-CGH analysis can visit our
     web-page: <URL: http://bioinfo.curie.fr>.

_A_u_t_h_o_r(_s):

     Pierre Neuvial, manor@curie.fr.

_S_e_e _A_l_s_o:

     'genome.plot', 'arrayPlot', 'html.report'

_E_x_a_m_p_l_e_s:

     data(spatial)

     ### edge: local spatial bias
     ## aggregate arrayCGH without normalization for comparison with
     ## normalized array
     edge.nonorm <- norm(edge, flag.list=NULL, FUN=median, na.rm=TRUE) 
     edge.nonorm <- sort(edge.nonorm, position.var="PosOrder")

     layout(matrix(c(1,2,4,5,3,3,6,6), 4,2),width=c(1, 4), height=c(6,1,6,1))
     report.plot(edge.nonorm, chrLim="LimitChr", layout=FALSE,
     main="Pangenomic representation (before normalization)", zlim=c(-1,1),
     ylim=c(-3,1))  
     report.plot(edge.norm, chrLim="LimitChr", layout=FALSE,
     main="Pangenomic representation (after normalization)", zlim=c(-1,1),
     ylim=c(-3,1)) 

     ### gradient: global array Trend
     ## aggregate arrayCGH without normalization for comparison with
     ## normalized array
     gradient.nonorm <- norm(gradient, flag.list=NULL, FUN=median, na.rm=TRUE) 
     gradient.nonorm <- sort(gradient.nonorm)

     layout(matrix(c(1,2,4,5,3,3,6,6), 4,2),width=c(1, 4), height=c(6,1,6,1))
     report.plot(gradient.nonorm, chrLim="LimitChr", layout=FALSE,
     main="Pangenomic representation (before normalization)", zlim=c(-2,2),
     ylim=c(-3,2)) 
     report.plot(gradient.norm, chrLim="LimitChr", layout=FALSE,
     main="Pangenomic representation (after normalization)", zlim=c(-2,2),
     ylim=c(-3,2)) 

