qscores                package:MANOR                R Documentation

_E_x_a_m_p_l_e_s _o_f _q_s_c_o_r_e _o_b_j_e_c_t_s (_q_u_a_l_i_t_y _s_c_o_r_e_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 'qscore' objects that can be applied to
     _normalized_ 'arrayCGH' objects in order to evaluate data quality
     after normalization.

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

     data(qscores)

_F_o_r_m_a_t:

     The following 'qscore' objects are provided:

         'clone.qscore'            number of clones
         'pct.clone.qscore'        percentage of clones
         'pct.spot.qscore'         percentage of spots
         'pct.spot.before.qscore'  percentage of spots before normalization
         'pct.replicate.qscore'    average percentage of replicates
         'smoothness.qscore'       signal smoothness
         'var.replicate.qscore'    
         'dyn.x.qscore'            signal dynamics on X chromosome
         'dyn.y.qscore'            signal dynamics on Y chromosome

_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', 'qscore.summary.arrayCGH', 'qscore'

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

     data(qscores)
     data(spatial)

     ## define a list of qscores
     qscore.list <- list(clone=clone.qscore, pct.clone=pct.clone.qscore,
     pct.spot=pct.spot.qscore, pct.replicate=pct.replicate.qscore,
     smoothness=smoothness.qscore, dyn.x=dyn.x.qscore, dyn.y=dyn.y.qscore,
     var.replicate=var.replicate.qscore)

     ## compute quality scores for a couple of normalized arrays
     gradient.norm$quality <- qscore.summary.arrayCGH(gradient.norm,
     qscore.list)
     print(gradient.norm$quality[, 2:3])

     qscore.list$dyn.x$args$test <- 23
     qscore.list$dyn.y$args$test <- 24
     edge.norm$quality <- qscore.summary.arrayCGH(edge.norm, qscore.list)
     print(edge.norm$quality[, 2:3])

