nem                   package:nem                   R Documentation

_N_e_s_t_e_d _E_f_f_e_c_t_s _M_o_d_e_l_s - _m_a_i_n _f_u_n_c_t_i_o_n

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

     The main function to infer a phenotypic hierarchy from data

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

     nem(D,inference="pairwise",models=NULL,type="mLL",para=NULL,hyperpara=NULL,Pe=NULL,Pm=NULL,local.prior.size=length(unique(colnames(D))),local.prior.bias=1,verbose=TRUE)

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

       D: binary data matrix with experiments in the columns

inference: 'search' by function 'score()'; or 'pairwise' to use
          function 'pairwise.posterior()'

  models: a list of adjacency matrices for model search. If NULL,
          'enumerate.models' is used for exhaustive enumeration of all
          possible models.

    type: 'mLL' or 'FULLmLL'

    para: vector of length two: false positive rate and false negative
          rate. Used by 'mLL()'

hyperpara: vector of length four: used by 'FULLmLL()'

      Pe: prior of effect reporter positions in the phenotypic
          hierarchy

      Pm: prior over models. For pairwise learning generated by
          'local.model.prior()' according to arguments
          'local.prior.size' and 'local.prior.bias'

local.prior.size: prior expected number of edges in the graph

local.prior.bias: bias towards double-headed edges. Default: 1 (no
          bias)

 verbose: do you want to see progression statements" Default: TRUE

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

     'nem' is an interface to the functions 'score()' and
     'pairwise.posterior()'. 

     'plot.nem' plots the inferred phenotypic hierarchy as a directed
     graph, and 'print.nem' gives an overview over the 'nem' object.

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

     An object of class 'score' or class 'pairwise' containing slots 

   graph: the inferred phenotypic hierarchy

     pos: posterior distribution of positions of effect reporters

  mappos: estimated position of effects in the phenotypic hierarchy

     and additional ones according to the function used for inference.

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

     Florian Markowetz <URL: http://genomics.princeton.edu/~florian>

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

     'score', 'pairwise.posterior', 'local.model.prior',
     'enumerate.models'

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

        data("BoutrosRNAi2002")
        D <- BoutrosRNAiDiscrete[,9:16]
        res1 <- nem(D,para=c(.13,.05),inference="search")
        res2 <- nem(D,para=c(.13,.05),inference="pairwise")

        par(mfrow=c(1,2))
        plot(res1,main="by exhaustive search")
        plot(res2,main="by pairwise heuristic")
        

