qscore.summary             package:MANOR             R Documentation

_C_o_m_p_u_t_e _q_u_a_l_i_t_y _s_c_o_r_e_s _f_o_r _a _g_i_v_e_n _a_r_r_a_y_C_G_H _o_b_j_e_c_t

_D_e_s_c_r_i_p_t_i_o_n:

     Compute useful quality scores for the 'arrayCGH' and display them
     in a convenient way

_U_s_a_g_e:

     qscore.summary.arrayCGH(arrayCGH, qscore.list)

_A_r_g_u_m_e_n_t_s:

arrayCGH: an object of type 'arrayCGH'

qscore.list: a list of objects of type 'qscore'

_D_e_t_a_i_l_s:

     This function is used by the function 'html.report' for the
     generation of an HMTL report of the normalization step. It can
     also be used by itself.

_V_a_l_u_e:

     A data.frame with 3 columns: 

    name: qscore name

   label: qscore label

  qscore: quality qscore

_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:

     'qscore', 'qscore.summary', 'html.report'

_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])

