pairwise.comparison        package:simpleaffy        R Documentation

_C_o_m_p_u_t_e _p_a_i_r_w_i_s_e _c_o_m_p_a_r_i_s_o_n _s_t_a_t_i_s_t_i_c_s _b_e_t_w_e_e_n _t_w_o _e_x_p_e_r_i_m_e_n_t_a_l _g_r_o_u_p_s

_D_e_s_c_r_i_p_t_i_o_n:

     Generate fold changes, t-tests and means for a pair of
     experimental groups

_U_s_a_g_e:

       pairwise.comparison(x,group,members=NULL,spots=NULL,a.order=NULL,b.order=NULL,method="unlogged",logged=TRUE)

_A_r_g_u_m_e_n_t_s:

       x: an exprSet object 

   group: column in pData(x) 

 members: labels in group 

   spots: unnormalised AffyBatch data for this experiment - if
          included, results in PMA calls and detection p-values being
          generated 

 a.order: For a comparison with matched pairs, the ordering of the
          first group of replicates

 b.order: For a comparison with matched pairs, the ordering of the
          second group of replicates

  method: What method should be used to calculate the average for the
          fold-change - can be either "logged","unlogged","median" 

  logged: Whether the input data is logged or not 

_D_e_t_a_i_l_s:

     Given an exprSet object, generate quick stats for pairwise
     comparisons between a pair of experimental groups. If a.order and
     b.order are specified then a paired sample t-test will be
     conducted between the groups, with the arrays in each group sorted
     according to the ordering specified. By default, the function
     assumes that the expression values are logged (this can be changed
     with the parameter "logged"). The fold-changes are computed from
     the average values across replicates. Unless you specify
     otherwise, this is done using the mean of the unlogged values
     (i.e. logged data is first unlogged, the mean calculated, and the
     result re-logged). The parameter "method", allows the mean of the
     logged values or their median to be used instead. T-tests are
     always computed with the logged data.

_V_a_l_u_e:

     A Pairwise comparison object.

_A_u_t_h_o_r(_s):

     Crispin J Miller

_R_e_f_e_r_e_n_c_e_s:

     http://bioinformatics.picr.man.ac.uk/

_E_x_a_m_p_l_e_s:

      
       ## Not run: 
         pc <- pairwise.comparison(eset.rma,"group",c("A","P")) 
       
     ## End(Not run)