simScore                package:cosmo                R Documentation

_S_c_o_r_e _m_o_t_i_f _d_e_t_e_c_t_i_o_n _s_i_m_u_l_a_t_i_o_n _r_e_s_u_l_t_s

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

     This function computes sensitivity and specifity for the results
     returned by cosmo.

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

       simScore(truth, cosmoOut, minOverlap=0.25)

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

   truth: 'align' Alignment describing the true motif occurrences.

cosmoOut: 'cosmo' The results returned by 'cosmo()'.

minOverlap: 'numeric' A predicted motif must overlap at least this
          proportion of a known motif to be considered a hit.

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

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

    sens: The proportion of true motif occurrences discovered
          (sensitivity).

    spec: The proportion of true motif occurrences among the discovered
          sites (specificity).

     roc: The area under the ROC curve.

_N_o_t_e:

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

     Oliver Bembom, bembom@berkeley.edu

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

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

     'cosmo'

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

     ## generate 20 sequences according to OOPS model
     ## with an expected 50
     ## motif
     data(motifPWM)
     data(transMats)
     res <- rseq(20, 100, 1.0, motifPWM, transMats,"ZOOPS")
     truth <- res$motifs
     seqs <- res$seqs

     res <- cosmo(seqs, constraints="None", minW=8, maxW=8)
     simScore(truth, res)

