FindA0class             package:siggenes             R Documentation

_C_l_a_s_s _F_i_n_d_A_0

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

     This is a class representation for the specification of the fudge
     factor in an EBAM analysis as proposed by Efron et al. (2001).

_O_b_j_e_c_t_s _f_r_o_m _t_h_e _C_l_a_s_s:

     Objects can be created using the function 'find.a0'.

_S_l_o_t_s:


     '_m_a_t._z': Object of class '"matrix"' containing the expression
          scores of the genes for each of the possible values for the
          fudge factor, where each row corresponds to a gene, and each
          column to one of the values for the fudge factor a0.

     '_m_a_t._p_o_s_t_e_r_i_o_r': Object of class '"matrix"' consisting of the
          posterior probabilities of the genes for each of the possible
          values  for the fudge factor, where each row of
          'mat.posterior' corresponds to a gene, and each column to one
          of the values for a0. The  probabilities in 'mat.posterior'
          are computed using the monotonically transformed test scores
          (see the Details section of 'find.a0')

     '_m_a_t._c_e_n_t_e_r': Object of class '"matrix"' representing the centers
          of the 'nrow(mat.center)' intervals used in the logistic
          regression with repeated observations for estimating f/f0 for
          each of the 'ncol(mat.center)' possible values for the fudge 
          factor.

     '_m_a_t._s_u_c_c_e_s_s': Object of class '"matrix"' consisting of  the
          numbers of observed test scores in the 'nrow(mat.success)'
          intervals used in the logistic regression with repeated
          observations for each of the 'ncol(mat.success)' possible
          values for the fudge factor.

     '_m_a_t._f_a_i_l_u_r_e': Object of class '"matrix"' containing the numbers
          of permuted test scores in the 'nrow(mat.failure)' intervals
          used in the logistic regression with repeated observations
          for each of the 'ncol(mat.failure)' possible values for the
          fudge factor.

     '_z._n_o_r_m': Object of class '"numeric"' comprising the values of the
          'nrow(mat.z)' quantiles of the standard normal  distribution
          (if any 'mat.z<0') or an F-distribution (if all 'mat.z>=0').

     '_p_0': Object of class '"numeric"' specifying the prior probability
          that a gene is not differentially expressed.

     '_m_a_t._a_0': Object of class '"data.frame"' comprising the number of
          differentially expressed genes and the estimated FDR for the
          possible choices of the fudge factor specified by 'vec.a0'.

     '_m_a_t._s_a_m_p': Object of class '"matrix"' consisting of the
          'nrow{mat.samp}' permutations of the class labels.

     '_v_e_c._a_0': Object of class '"numeric"' representing the possible
          values of the fudge factor a0.

     '_s_u_g_g_e_s_t_e_d': Object of class '"numeric"' revealing the suggested
          choice for the fudge factor, i.e. the value of 'vec.a0' that
          leads to the largest number of differentially expressed
          genes.

     '_d_e_l_t_a': Object of class '"numeric"' specifying the minimum
          posterior probability that a gene must have to be called 
          differentially expressed.

     '_d_f._r_a_t_i_o': Object of class '"numeric"' representing the degrees
          of freedom of the natural cubic spline used in the logistic
          regression with repeated observations.

     '_m_s_g': Object of class '"character"' containing information about,
          e.g., the type of analysis. 'msg' is printed when  'print' is
          called.

     '_c_h_i_p': Object of class '"character"' naming the microarray used
          in the analysis. If no information about the chip is
          available, 'chip' will be set to '""'.

_M_e_t_h_o_d_s:


     _p_l_o_t 'signature(object = "FindA0")': Generates a plot of the
          (logit-transformed) posterior probabilities of the genes for
          a specified  value of Delta and a set of possible values for
          the fudge factor. For details, see 'help.finda0(plot)'. For
          the arguments, see 'args.finda0(plot)'.

     _p_r_i_n_t 'signature(object = "FindA0)': Prints the number of 
          differentially expressed genes and the estimated FDR for each
          of the possible values of the fudge factor specified by 
          'vec.a0'. For details, see 'help.finda0(print)'.  For
          arguments, see 'args.finda0(print)'. 

     _s_h_o_w 'signature(object = "FindA0")': Shows the output of an
          analysis with 'find.a0'.

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

     Holger Schwender, holger.schw@gmx.de

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

     Efron, B., Tibshirani, R., Storey, J.D. and Tusher, V. (2001).
     Empirical Bayes Analysis of a Microarray Experiment, _JASA_, 96,
     1151-1160.

     Schwender, H., Krause, A. and Ickstadt, K. (2003). Comparison of
     the Empirical Bayes and the Significance Analysis of Microarrays.
     _Technical Report_, SFB 475, University of Dortmund, Germany.

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

     'find.a0', 'ebam', 'EBAM-class'

