cghMCR-class             package:cghMCR             R Documentation

_C_l_a_s_s "_c_g_h_M_C_R" _i_s _a _S_4 _c_l_a_s_s _f_o_r _t_h_e _i_d_e_n_t_i_f_i_c_a_t_i_o_n _o_f _m_i_n_i_m_u_m
_c_o_m_m_o_n _r_e_g_i_o_n_s _o_f _g_a_i_n_s _o_r _l_o_s_s_e_s _a_c_r_o_s_s _s_a_m_p_l_e_s

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

     Objects of this class provides the functionalities to detecting
     chromosome regions that show gains or losses across differnet
     samples

_O_b_j_e_c_t_s _f_r_o_m _t_h_e _C_l_a_s_s:

     Objects can be created by calls of the form 'new("cghMCR", ...)'.
     A constructor 'cghMCR' may be used to instantiate object of this
     class

_S_l_o_t_s:

     '_D_N_A_S_e_g': Object of class '"data.frame"' containing segmentation
          data derived from segmentation analysis using segment or
          'getSegments'

     '_m_a_r_g_i_n': Object of class '"numeric"' indicating how far apart two
          adjacent segments are allowed to be considered to be of the
          same locus

     '_g_a_i_n._t_h_r_e_s_h_o_l_d': Object of class '"numeric"' specificing the
          value of log2 ratio for chromosome gains

     '_l_o_s_s._t_h_r_e_s_h_o_l_d': Object of class '"numeric"' specificing the
          value of negative log2 ratio for chromosome losses

_M_e_t_h_o_d_s:

     _M_C_R 'signature(object = "cghMCR")': identifies minimum common
          regions of gains/losses across samples

_N_o_t_e:

     The function is a contribution of The Center for Applied Cancer
     Science of Dana-Farber Cancer Institute

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

     Jianhua Zhang

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

_S_e_e _A_l_s_o:

     'cghMCR'

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

       require("cghMCR")
       data("sampleData")
       segments <- getSegments(sampleData)
       cghmcr <- cghMCR(segments, margin = 0, gain.threshold = 0.8,
                      loss.threshold = -0.8)

