flags                 package:MANOR                 R Documentation

_E_x_a_m_p_l_e_s _o_f _f_l_a_g _o_b_j_e_c_t_s _t_o _a_p_p_l_y _t_o _C_G_H _a_r_r_a_y_s

_D_e_s_c_r_i_p_t_i_o_n:

     This data set provides 'flag' objects that can be applied to
     'arrayCGH' objects in order to normalize them.

_U_s_a_g_e:

     data(flags)

_F_o_r_m_a_t:

     These 'flag' objects typically take part to a normalization
     process:

         'amplicon.flag'        flags spots with high log-ratios (temp flag)
         'chromosome.flag'      flags spots located on sexual chromosomes (named "X" and "Y")
         'control.flag'         flag control spots
         'global.spatial.flag'  corrects arrayCGH from global spatial trend on the array
         'local.spatial.flag'   flags spots belonging to local spatial bias zones on the array
         'num.chromosome.flag'  flags spots located on sexual chromosomes (named 23 and 24)
         'position.flag'        flag spots with no available genome position
         'replicate.flag'       flag spots with poor within-clone-replicate consitency
         'ref.snr.flag'         flags spots with low signal to noise ratio for reference
         'dapi.snr.flag'        flags spots with low signal to noise ratio for DAPI
         'SNR.flag'             flags spots with low signal to noise ratio
         'spot.corr.flag'       flags spots with low correlation coefficient after image analysis
         'spot.flag'            flags spots excluded by the image analysis software
         'unique.flag'          exclude last non-flagged spot of a clone
         'val.mark.flag'        flags spots corresponding to bad quality clones
         'intensity.flag'       corrects for an intensity effect (using loess regression)

_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_o_u_r_c_e:

     Institut Curie, manor@curie.fr.

_S_e_e _A_l_s_o:

     'spatial', 'norm.arrayCGH', 'flag', 'flag.summary'

_E_x_a_m_p_l_e_s:

     data(flags)

     ### complete normalization of an arrayCGH object (with spatial gradient):
     ## Initialize flag$args

     flag.list1 <- list(local.spatial=local.spatial.flag,
       global.spatial=global.spatial.flag, spot=spot.flag, SNR=SNR.flag,
       val.mark=val.mark.flag, unique=unique.flag,
       amplicon=amplicon.flag, chromosome=chromosome.flag,
       replicate=replicate.flag)

     data(spatial)
     ## Not run: 
     gradient.norm <- norm.arrayCGH(gradient, flag.list=flag.list1,
     var="LogRatio", FUN=median, na.rm=TRUE)
     ## End(Not run)
     print(gradient.norm$flags) ## spot-level flag summary (computed by flag.summary)

     ### complete normalization of an arrayCGH object (with local spatial bias):
     ## Initialize flag$args

     flag.list2 <- list(spatial=local.spatial.flag, spot=spot.corr.flag,
     ref.snr=ref.snr.flag, dapi.snr=dapi.snr.flag, rep=rep.flag,
     unique=unique.flag) 
     flag.list2$spatial$args <- alist(var="ScaledLogRatio", by.var=NULL,
     nk=5, prop=0.25, thr=0.15, beta=1, family="symmetric") 
     flag.list2$spot$args <- alist(var="SpotFlag")
     flag.list2$spot$char <- "O"
     flag.list2$spot$label <- "Image analysis"

     ## Not run: 
     edge.norm <- norm.arrayCGH(edge, flag.list=flag.list2,
     var="LogRatio", FUN=median, na.rm=TRUE)
     ## End(Not run) 
     print(edge.norm$flags) ## spot-level flag summary (computed by flag.summary)

