plot-methods              package:lumi              R Documentation

_P_l_o_t _o_f _a _L_u_m_i_B_a_t_c_h _o_b_j_e_c_t

_D_e_s_c_r_i_p_t_i_o_n:

     Creating quality control plots of a LumiBatch object

_U_s_a_g_e:

     ## S4 method for signature 'LumiBatch, missing':
     plot(x, what = c("density", "boxplot", "pair", "MAplot", "sampleRelation", "outlier", "cv"), main, ...)

_A_r_g_u_m_e_n_t_s:

       x: a LumiBatch object returned by 'lumiQ' 

    what: one of the six kinds of QC plots 

    main: the title of the QC plot 

     ...: additional parameters for the corresponding QC plots 

_D_e_t_a_i_l_s:

     The parameter "what" of 'plot' function controls the type of QC
     plots, which includes:

     *_d_e_n_s_i_t_y*: the density plot of the chips, see 'hist-methods'

     *_b_o_x_p_l_o_t*: box plot of the chip intensities, see 'boxplot-methods'

     *_p_a_i_r*: the correlation among chips, plot as a hierarchical tree,
          see 'pairs-methods'

     *_M_A_p_l_o_t*: the MAplot between chips, see 'MAplot-methods'

     *_s_a_m_p_l_e_R_e_l_a_t_i_o_n*: plot the sample relations. See
          'plotSampleRelation'

     *_o_u_t_l_i_e_r*: detect the outliers based on the sample distance to the
          center. See  'detectOutlier'

     *_c_v*: the density plot of the coefficients of variance of the
          chips. See 'estimateLumiCV'

_S_e_e _A_l_s_o:

     'LumiBatch-class', 'hist-methods', 'boxplot-methods',
     'MAplot-methods', 'pairs-methods', 'plotSampleRelation',
     'estimateLumiCV', 'detectOutlier'

_E_x_a_m_p_l_e_s:

     ## load example data
     data(example.lumi)

     ## Quality control estimation
     lumi.Q <- lumiQ(example.lumi)

     ## summary
     summary(lumi.Q)

     ## plot the density
     plot(lumi.Q, what='density')

     ## plot the pairwise sample correlation
     plot(lumi.Q, what='pair')

     ## plot the pairwise MAplot
     plot(lumi.Q, what='MAplot')

     ## sample relations
     plot(lumi.Q, what='sampleRelation', method='mds', color=c('100US', '95US:5P', '100US', '95US:5P'))

     ## detect outlier based on the distance to the mean profile
     plot(lumi.Q, what='outlier')

     ## Density plot of coefficient of variance
     plot(lumi.Q, what='cv')

