gcrma                 package:gcrma                 R Documentation

_R_o_b_u_s_t _M_u_l_t_i-_A_r_r_a_y _e_x_p_r_e_s_s_i_o_n _m_e_a_s_u_r_e _u_s_i_n_g _s_e_q_u_e_n_c_e _i_n_f_o_r_m_a_t_i_o_n

_D_e_s_c_r_i_p_t_i_o_n:

     This function converts an 'AffyBatch' into an 'ExpressionSet'
     using the robust multi-array average (RMA) expression measure with
     help of probe sequence.

_U_s_a_g_e:

     gcrma(object,affinity.info=NULL,
           affinity.source=c("reference","local"),NCprobe=NULL,
           type=c("fullmodel","affinities","mm","constant"),
           k=6*fast+0.5*(1-fast),stretch=1.15*fast+1*(1-fast),correction=1,
           GSB.adjust=TRUE,
           rho=.7,optical.correct=TRUE,verbose=TRUE,fast=TRUE,
           subset=NULL,normalize=TRUE,...)

_A_r_g_u_m_e_n_t_s:

  object: an 'AffyBatch'

affinity.info: 'NULL' or an 'AffyBatch' containing the affinities in
          the 'exprs' slot. This object can be created using the
          function 'compute.affinities'.

affinity.source: 'reference': use the package internal Non-specific
          binding data or 'local': use the experimental data in
          'object'. If 'local' is chosen, either MM probes or a
          user-defined list of probes (see 'NCprobes') are used to
          estimate affinities.

 NCprobe: Index of negative control probes. When set as 'NULL',the MM
          probes will be used. These probes are used to estimate
          parameters of non-specific binding on each array. These will
          be also used to estimate probe affinity profiles when
          affinity.info is not provided.

    type: "fullmodel" for sequence and MM model. "affinities" for
          sequence information only. "mm" for using MM without sequence
          information.

       k: A tuning factor.

 stretch: 

correction: .

GSB.adjust: Logical value. If 'TRUE', probe effects in specific binding
          will be adjusted.

     rho: correlation coefficient of log background intensity in a pair
          of pm/mm probes. Default=.7

optical.correct: Logical value. If 'TRUE', optical background
          correction is performed.

 verbose: Logical value. If 'TRUE' messages about the progress of the
          function is printed.

    fast: Logical value. If 'TRUE' a faster ad hoc algorithm is used.

  subset: a character vector with the the names of the probesets to be
          used in expression calculation.

normalize: logical value. If 'TRUE' normalize data using quantile
          normalization.

     ...: further arguments to be passed (not currently implemented -
          stub for future use).

_D_e_t_a_i_l_s:

     Note that this expression measure is given to you in log base 2
     scale. This differs from most of the other expression measure
     methods.

     The tuning factor 'k' will have different meanings if one uses the
     fast (add-hoc) algorithm or the empirical Bayes approach. See Wu
     et al. (2003)

_V_a_l_u_e:

     An 'ExpressionSet'.

_A_u_t_h_o_r(_s):

     Rafeal Irizarry

_E_x_a_m_p_l_e_s:

     if(require(affydata) & require(hgu95av2probe) & require(hgu95av2cdf)){
          data(Dilution)
          ai <- compute.affinities(cdfName(Dilution))
          Dil.expr<-gcrma(Dilution,affinity.info=ai,type="affinities")
     }