nem.discretize              package:nem              R Documentation

_D_i_s_c_r_e_t_i_z_e _p_e_r_t_u_r_b_a_t_i_o_n _d_a_t_a _a_c_c_o_r_d_i_n_g _t_o _c_o_n_t_r_o_l _e_x_p_e_r_i_m_e_n_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     discretizes raw data to define effects of interventions with
     respect to wildtype/control measurements

_U_s_a_g_e:

     nem.discretize(D,neg.control=NULL,pos.control=NULL,nfold=2,cutoff=0:10/10, pCounts=20, empPval=.05, verbose=TRUE)

_A_r_g_u_m_e_n_t_s:

       D: matrix with experiments as columns and effect reporters as
          rows

neg.control: either indices of columns in 'D' or a matrix with the same
          number of rows as 'D'

pos.control: either indices of columns in 'D' or a matrix with the same
          number of rows as 'D'

   nfold: fold-change between neg. and pos. controls for selecting
          effect reporters. Default: 2

  cutoff: a (vector of) cutoff value(s) weighting the pos. controls
          versus the neg. controls. Default: 0:10/10

 pCounts: pseudo-counts to guard against unreasonable low error
          estimates

 empPval: empirical p-value cutoff for effects if only one control is
          available

 verbose: Default: TRUE

_D_e_t_a_i_l_s:

     Chooses cutoff such that separation between negative and positive
     controls becomes optimal.

_V_a_l_u_e:

     dat: discretized data matrix

     pos: discretized positive controls [in the two-controls setting]

     neg: discretized negative controls [in the two-controls setting]

     sel: effect reporters selected [in the two-controls setting]

  cutoff: error rates for different cutoff values [in the two-controls
          setting]

    para: estimated error rates [in the two-controls setting]

_N_o_t_e:

     preliminary! will be developed to be more generally applicable

_A_u_t_h_o_r(_s):

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

_R_e_f_e_r_e_n_c_e_s:

     Markowetz F, Bloch J, Spang R, Non-transcriptional pathway
     features reconstructed from secondary effects of RNA interference,
     Bioinformatics, 2005

_S_e_e _A_l_s_o:

     'BoutrosRNAi2002'

_E_x_a_m_p_l_e_s:

        # discretize Boutros data as in
        # Markowetz et al, 2005
        data("BoutrosRNAi2002")
        disc <- nem.discretize(BoutrosRNAiExpression,neg.control=1:4,pos.control=5:8,cutoff=.7)
        stopifnot(disc$dat==BoutrosRNAiDiscrete[,9:16])   

