relNet2TGF            package:maigesPack            R Documentation

_T_r_a_n_s_f_o_r_m _R_e_l_e_v_a_n_c_e _N_e_t_w_o_r_k _a_n_a_l_y_s_i_s _i_n _T_G_F _o_u_t_p_u_t

_D_e_s_c_r_i_p_t_i_o_n:

     This function receive an object of class 'maigesRelNetB' or
     'maigesRelNetM' and write TGF files with the relevance networks
     produced.

_U_s_a_g_e:

     relNet2TGF(...)

     ## S3 method for class 'maigesRelNetB':
     relNet2TGF(data, dir = "./",
       filename="group.tgf", corC=NULL, pValue=0.05, ...)

     ## S3 method for class 'maigesRelNetM':
     relNet2TGF(data, dir = "./",
       filenames=c("group1.tgf", "group2.tgf", "difPvalue.tgf"),
       pValue=0.05, ...)

_A_r_g_u_m_e_n_t_s:

    data: object of class 'maigesRelNetB' or 'maigesRelNetM'.

     dir: character string specifying the folder to save the TGF files.

filename: character string specifying the file name, for objects of
          class 'maigesRelNetB'.

filenames: character vector of length 3 with the file names to be
          saved, for objects of class 'maigesRelNetM'.

    corC: numeric in [0,1] specifying the cutoff for selecting absolute
          correlation. May also be 'max' to select the maximum
          correlation values in a permutation bootstrap strategy, as
          proposed by Butte et al. (2000).

  pValue: numeric in [0,1] specifying the cutoff for selecting
          correlation values by p-values.

     ...: additional parameters.

_D_e_t_a_i_l_s:

     This function only picks the result of the 'relNetworkB' or
     'relNetworkM' and display write TGF files. This files are
     interesting to be used with _Yed_ graph visualisation and editing
     tool, wrote in Java (<URL:
     http://www.yworks.com/en/products_yed_about.htm>).

_V_a_l_u_e:

     This function don't return any object.

_A_u_t_h_o_r(_s):

     Gustavo H. Esteves <gesteves@vision.ime.usp.br>

_R_e_f_e_r_e_n_c_e_s:

     Butte, A.J.; Tamayo, P.; Slonim, D.; Golub, T.R. and Kohane, I.S.
     Discovering functional relationships between RNA expression and
     chemotherapeutic susceptibility using relevance networks, *PNAS*,
     97, 12182-12186, 2000 (<URL:
     http://www.pnas.org/cgi/content/full/97/22/12182>)

_S_e_e _A_l_s_o:

     'relNetworkB', 'relNetworkM', 'maigesRelNetB', 'maigesRelNetM'.

_E_x_a_m_p_l_e_s:

     ## Loading the dataset
     data(gastro)

     ## Constructing the relevance network for sample
     ## 'Tissue' comparing 'Neso' and 'Aeso' for the 1st gene group
     ## The same is also true for objects of class maigesRelNetB
     gastro.net = relNetworkM(gastro.summ, sLabelID="Tissue", 
       samples = list(Neso="Neso", Aeso="Aeso"), geneGrp=11,
       type="Rpearson")

     relNet2TGF(gastro.net)

