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 `exprSet' using the
     robust multi-array average (RMA) expression measure with help of
     probe sequence.

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

     gcrma(object,estimate="eb",summary.method = "rlm",summary.subset=geneNames(object)[1:10]),...)

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

  object: an 'AffyBatch'

estimate: "eb" or "mle". An character indicating background correction
          method. "eb" for empirical Bayes, "mle" for maximum
          likelihood

summary.method: "medianpolish" or "rlm". Method to extract the
          expression value of a probeset from  background adjusted
          intensities. 

normalize: logical value. If 'TRUE' normalize data using
          normalize.method (default as quantile normalization)

     rho: correlation coefficient of log background intensity in a pair
          of pm/mm probes. Default=.8

triple.goal: 

baseline: For estimate="mle" only. The lowest log(expression) value
          allowed. Default=.25

lower.bound: For estimate="eb" only. Lower bound of signal intensity
          allowed a priori. Default=1.

    step: a parameter in approximating "eb" estimates.

_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.

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

     An `exprSet'

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

     Jean Wu, Rafeal Irizarry

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

     Wei Shen and Thomas Louis.  Triple-goal estimates in two-stage
     hierarchical models. J.R.Statist.Soc.B(1998)

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

     require(affydata)
     data(Dilution)
     Dil.expr<-gcrma(Dilution,estimate="mle",summary.method = "medianpolish",summary.subset=geneNames(Dilution)[1:10])

