clin2mim                package:SAGx                R Documentation

_O_u_t_p_u_t _a _s_c_r_i_p_t _f_i_l_e _t_o _W_i_n_M_I_M, _l_i_n_k_i_n_g _c_l_i_n_i_c_a_l _d_a_t_a _a_n_d _g_e_n_e _e_x_p_r_e_s_s_i_o_n

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

     Given a clinical variable, it produces a script file for WinMIM by
     calculating means and covariances and  for the N most highly
     correlated probes (in absolute value). Here N is an input
     parameter, but a recommended value 10. WinMIM can find a relevant
     graphical model for the dependencies between the probes and the
     clinical variable.

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

     clin2mim(variable="FEV1.ACTUAL",data=dbs,clindat=clinical,probes=probes,N=10,out="mimscr.txt")

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

variable: Clinical variable to be examined

    data: The input data set, with subject id in first column.

 clindat: The input clinical data, with subject id in first column

  probes: The name of the probes in the order of _data_

       N: The number of highly correlated probes to be studied

     out: The MIM script file

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

     The correlation matrix

_N_o_t_e:

     David Edwards' program WinMIM can be found on  StatLib (<URL:
     http://lib.stat.cmu.edu/graphmod/>). In MIM issue 'input
     mimscript.txt' and the calculations to find a model will start.
     When finished go to the Graphics menu and  click on 'Independence
     Graph'. The resulting graph can be exported both to WMF and LaTeX.

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

     Per Broberg

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

     Edwards, David (1995) _Introduction to Graphical Modelling_.
     Springer-Verlag 
      Lautitzen, Steffen (1996) _Graphical Models_. Oxford University
     Press 
      Whittaker, Joe (1990) _Graphical Models in Multivariate
     Analysis_. Wiley 

