qc                package:simpleaffy                R Documentation

_G_e_n_e_r_a_t_e _Q_C _s_t_a_t_s _f_r_o_m _a_n _A_f_f_y_B_a_t_c_h _o_b_j_e_c_t

_D_e_s_c_r_i_p_t_i_o_n:

     Generate QC metrix for Affymetrix data.

_U_s_a_g_e:

     qc(unnormalised, ...)

_A_r_g_u_m_e_n_t_s:

unnormalised: An AffyBatch object with nowt done to it 

     ...: Any other parameters 

_D_e_t_a_i_l_s:

     Affymetrix recommend a series of QC metrics that should be used to
     check that arrays have hybridised correctly and that sample
     quality is acceptable. These are discussed in the document 'QC and
     Affymetrix data' accompanying this package, and on the web at
     http://bioinformatics.picr.man.ac.uk. They are described in detail
     in the 'Expression Analysis Fundamentals' manual available from
     Affymetrix.

     Before using this function you are strongly encouraged to read the
     'QC and Affymetrix data' document, which contains detailed
     examples.

     This function takes an 'AffyBatch' object and generates a
     'QCStats' object containing a set of QC metrics. See 'qc.affy' for
     more details.

_A_u_t_h_o_r(_s):

     Crispin J Miller

_S_e_e _A_l_s_o:

     'qc.affy' 'setQCEnvironment'

_E_x_a_m_p_l_e_s:

       ## Not run: 
         qcs <- qc(eset,eset.mas)
       
     ## End(Not run)
       data(qcs)
       ratios(qcs)
       avbg(qcs)
       maxbg(qcs)
       minbg(qcs)
       spikeInProbes(qcs)
       qcProbes(qcs)
       percent.present(qcs)
       plot(qcs)
       sfs(qcs)
       target(qcs)
       ratios(qcs)