proboStruct-class         package:MAQCsubset         R Documentation

_C_l_a_s_s "_p_r_o_b_o_S_t_r_u_c_t"

_D_e_s_c_r_i_p_t_i_o_n:

     structure for managing proboscis plot data

_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("proboStruct",
     ...)'.

_S_l_o_t_s:

     '._D_a_t_a': Object of class '"list"' ~~ 

     '_c_a_l_l': Object of class '"call"' ~~ 

_E_x_t_e_n_d_s:

     Class '"list"', from data part. Class '"vector"', by class "list",
     distance 2. Class '"AssayData"', by class "list", distance 2.

_M_e_t_h_o_d_s:

     plot

_N_o_t_e:

     The proboscis plot shows how the  probability of self-consistent
     monotone titration  (SCMT) varies with the spiked difference in
     concentrations of two mRNA preparations in an MAQC dataset.

_A_u_t_h_o_r(_s):

     V Carey <stvjc@channing.harvard.edu>

_R_e_f_e_r_e_n_c_e_s:

     For Figure 2 of Shippy et al., Using RNA sample titrations... (Nat
     Biotech, 24(9):1123-1131, Sep 2006)

_E_x_a_m_p_l_e_s:

     data(afxsubRMAES)
     NN1 = proboscis(afxsubRMAES)
     plot(NN1)
     showClass("proboStruct")

