CGHcall               package:CGHcall               R Documentation

_C_a_l_l_i_n_g _a_b_e_r_r_a_t_i_o_n_s _f_o_r _a_r_r_a_y _C_G_H _t_u_m_o_r _p_r_o_f_i_l_e_s.

_D_e_s_c_r_i_p_t_i_o_n:

     Calls aberrations for array CGH data using a six state mixture
     model.

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

     CGHcall(inputSegmented, prior = "auto", nclass = 3, organism = "human")

_A_r_g_u_m_e_n_t_s:

inputSegmented: An object of class 'cghSeg' 

   prior: Options are 'all', 'not all', or 'auto'. See details for more
          information. 

  nclass: The number of levels to be used for calling. Either '3'
          (loss, normal, gain) or '4' (including amplifications). 

organism: Either 'human' or 'other'. This is only used for chromosome
          arm information when 'prior' is set to 'all' or 'auto' (and
          samplesize > 20). 

_D_e_t_a_i_l_s:

     Please read the article and the supplementary information for
     detailed information on the algorithm. 

     The parameter 'prior' states how the data is used to determine the
     prior probabilities. When set to 'all', the probabilities are
     determined using the entire genome of each sample. When set to
     'not all' probabilites are determined per chromosome for each
     sample when 'organism' is set to 'other' or per chromosome arm
     when 'organism' is 'human'. The chromosome arm information is
     taken from the March 2006 version of the UCSC database. When
     'prior' is set to 'auto', the way probabilities are determined
     depends on the sample size. The entire genome is used when the
     sample size is smaller than 20, otherwise chromosome (arm)
     information is used.

     Please note that CGHcall uses information from all input data to
     determine the aberration probabilities. When for example triploid
     or tetraploid tumors are observed, we advise to run CGHcall
     separately on those (groups of) samples.

_V_a_l_u_e:

     This function return a list with three components: 

probabilities : A dataframe with 3 columns of probe information (name,
          chromosome and position), followed by k columns with
          aberration probabilities for each sample, where k is the
          number of levels used for calling ('nclass').

  calls : A dataframe with the calls for each sample. Values are '-1'
          (loss), '0' (normal) or '1' (gain). If 4 levels were used for
          calling, a value of '2' represents an amplification.

segments : A matrix with the segments for each profile. The first
          column contains the sample number. The second column the
          level of the current segment and the third and fourth columns
          the start and end of the segment in probe number
          respectively.

_A_u_t_h_o_r(_s):

     Sjoerd Vosse & Mark van de Wiel

_R_e_f_e_r_e_n_c_e_s:

     Mark A. van de Wiel, Kyung In Kim, Sjoerd J. Vosse, Wessel N. van
     Wieringen, Saskia M. Wilting and Bauke Ylstra. CGHcall: calling
     aberrations for array CGH tumor profiles. _Bioinformatics, 23_,
     892-894.

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

       data(WiltingSeg)
       ## Not run: result <- CGHcall(WiltingSeg)

