dyebias.umcu.proper.estimatorspackage:dyebiasexamplesR Documentation

_D_e_t_e_r_m_i_n_e _w_h_i_c_h _s_p_o_t_s _s_h_o_u_l_d _n_o_t _b_e _r_u_l_e_d _o_u_t _a_s _s_l_i_d_e _b_i_a_s _e_s_t_i_m_a_t_o_r_s

_D_e_s_c_r_i_p_t_i_o_n:

     Some spots (reporters/probes) should not be used when estimating
     the slide bias. Typical examples are mitochondrial genes and spots
     known to cross-hybridize. This function finds the ones that are OK
     to use.

_A_r_g_u_m_e_n_t_s:

reporter.info: A data.frame, one row per spot, with (at least) columns
          'reporterId' (e.g. gene id or oligo id) and any of the
          following characteristics: 'reporterGroup, chromosomeName,
          bioSeqType, crosshybRank and reporterSequence'.  They are
          used to get rid of reporters that are not suitable when
          estimating the slide bias. 

 verbose: Logical speficying whether to be verbose or not 

_D_e_t_a_i_l_s:

     This function is particular to the slides and database set-up at
     the Holstege lab, but might serve as inspiration.

_V_a_l_u_e:

     Returns and index vector that can be used as the
     'estimator.subset'-argument to 'dyebias.application.subset'.

_A_u_t_h_o_r(_s):

     Philip Lijnzaad p.lijnzaad@umcutrecht.nl

_R_e_f_e_r_e_n_c_e_s:

     Margaritis, T., Lijnzaad, P., van~Leenen, D., Bouwmeester, D.,
     Kemmeren, P., van~Hooff, S.R and Holstege, F.C.P. (2009) Adaptable
     gene-specific dye bias correction for two-channel DNA microarrays.
     _Molecular Systems Biology, submitted_

_S_e_e _A_l_s_o:

     'dyebias.apply.correction'

_E_x_a_m_p_l_e_s:

       

       ### choose the estimators and which spots to correct:
       estimator.subset <- dyebias.umcu.proper.estimators(maInfo(maGnames(data.norm)))

       summary(estimator.subset)

       ### do the correction
       ## Not run: 
          correction <- dyebias.apply.correction(data.norm=data.norm,
                                              iGSDBs = iGSDBs.estimated,
                                              estimator.subset=estimator.subset,
                                              application.subset = TRUE,
                                              verbose=TRUE)
        
     ## End(Not run)

