cghCall               package:CGHbase               R Documentation

_C_l_a_s_s _t_o _c_o_n_t_a_i_n _a_n_d _d_e_s_c_r_i_b_e _c_a_l_l_e_d _a_r_r_a_y _c_o_m_p_a_r_a_t_i_v_e _g_e_n_o_m_i_c _h_y_b_r_i_d_i_z_a_t_i_o_n _d_a_t_a.

_D_e_s_c_r_i_p_t_i_o_n:

     Container for aCGH data and experimental metadata. 'cghCall' class
     is derived from 'eSet', and requires the following matrices of
     equal dimension as assayData members:

        *  'copynumber' Log2 copynumber ratios.

        *  'segmented'  Segmented log2 ratios.

        *  'calls'                Called copynumer values.

        *  'probloss'           Loss probabilities as returned by
           'CGHcall'.

        *  'probnorm'           Normal probabilities as returned by
           'CGHcall'.

        *  'probgain'           Gain probabilities as returned by
           'CGHcall'.

        *  'probamp'            Optional amplification probabilities as
           returned by 'CGHcall' when run with 'nclass=4'.

     Furthermore, columns named 'Chromosome', 'Start', and 'End' are 
     required as featureData members, containing feature position
     information.

_E_x_t_e_n_d_s:

     Directly extends class 'eSet'.

_C_r_e_a_t_i_n_g _O_b_j_e_c_t_s:

     'new('cghCall', phenoData = [AnnotatedDataFrame], experimentData =
     [MIAME], annotation = [character], copynumber = [matrix],
     segmented = [matrix], calls = [matrix], probloss = [matrix],
     probnorm = [matrix], probgain = [matrix], featureData =
     [AnnotatedDataFrame], ...) '

     An object of class 'cghCall' is generally obtained as output from
     'CGHcall'.

_S_l_o_t_s:

     Inherited from 'eSet':

     '_a_s_s_a_y_D_a_t_a': Contains matrices with equal dimensions, and with
          column number equal to 'nrow(phenoData)'. 'assayData' must
          contain the following matrices

             *  'copynumber' Log2 copynumber ratios.

             *  'segmented'  Segmented log2 ratios.

             *  'calls'                Called copynumer values.

             *  'probloss'           Loss probabilities as returned by
                'CGHcall'.

             *  'probnorm'           Normal probabilities as returned
                by 'CGHcall'.

             *  'probgain'           Gain probabilities as returned by
                'CGHcall'.

             *  'probamp'            Optional amplification
                probabilities as returned by 'CGHcall' when run with
                'nclass=4'.

          with rows represening array probes and columns representing
          samples. Additional matrices of identical size (e.g.,
          representing measurement errors) may also be included in
          'assayData'. Class:'AssayData-class'

     '_p_h_e_n_o_D_a_t_a': See 'eSet'

     '_f_e_a_t_u_r_e_D_a_t_a': An 'AnnotatedDataFrame' with columns 'Chromosome',
          'Start', and 'End' containing array element position  data.

     '_e_x_p_e_r_i_m_e_n_t_D_a_t_a': See 'eSet'

     '_a_n_n_o_t_a_t_i_o_n': See 'eSet'

_M_e_t_h_o_d_s:

     Class-specific methods.

     '_c_o_p_y_n_u_m_b_e_r(_c_g_h_C_a_l_l)', '_c_o_p_y_n_u_m_b_e_r(_c_g_h_C_a_l_l,_m_a_t_r_i_x)<-' Access and
          set elements named 'copynumber' in the 'AssayData-class'
          slot.

     '_s_e_g_m_e_n_t_e_d(_c_g_h_C_a_l_l)', '_s_e_g_m_e_n_t_e_d(_c_g_h_C_a_l_l,_m_a_t_r_i_x)<-' Access and set
          elements named 'segmented' in the 'AssayData-class' slot.

     '_c_a_l_l_s(_c_g_h_C_a_l_l)', '_c_a_l_l_s(_c_g_h_C_a_l_l,_m_a_t_r_i_x)<-' Access and set
          elements named 'calls' in the 'AssayData-class' slot.

     '_p_r_o_b_l_o_s_s(_c_g_h_C_a_l_l)', '_p_r_o_b_l_o_s_s(_c_g_h_C_a_l_l,_m_a_t_r_i_x)<-' Access and set
          elements named 'probloss' in the 'AssayData-class' slot.

     '_p_r_o_b_n_o_r_m(_c_g_h_C_a_l_l)', '_p_r_o_b_n_o_r_m(_c_g_h_C_a_l_l,_m_a_t_r_i_x)<-' Access and set
          elements named 'probnorm' in the 'AssayData-class' slot.

     '_p_r_o_b_g_a_i_n(_c_g_h_C_a_l_l)', '_p_r_o_b_g_a_i_n(_c_g_h_C_a_l_l,_m_a_t_r_i_x)<-' Access and set
          elements named 'probgain' in the 'AssayData-class' slot.

     '_c_h_r_o_m_o_s_o_m_e_s', '_b_p_s_t_a_r_t', '_b_p_e_n_d' Access the chromosomal positions
          stored in 'featureData'

     _p_l_o_t._c_g_h_C_a_l_l Create a plot containing log2ratios, segments and
          call probabilities ordered by chromosomal position

     _s_u_m_m_a_r_y_P_l_o_t Create a plot summarizing the call probabilities of
          all samples

     See 'eSet' for derived methods.

_A_u_t_h_o_r(_s):

     Sjoerd Vosse

_S_e_e _A_l_s_o:

     'eSet-class', 'cghRaw-class', 'cghSeg-class'

_E_x_a_m_p_l_e_s:

             # create an instance of cghCall
             new("cghCall")
             
             # load an instance of cghCall
             data(WiltingCalled)
       
       # plot the first sample
       plot.cghCall(WiltingCalled[,1])
       
       # plot the first chromosome of the first sample
       plot.cghCall(WiltingCalled[chromosomes(WiltingCalled)==1,1])

       # get the copynumber values of the third and fourth sample
       log2ratios <- copynumber(WiltingCalled[,3:4])

       # get the names of the samples
       sampleNames(WiltingCalled)

       # get the names of the array elements
       featureNames(WiltingCalled)

