corPlot                package:Ringo                R Documentation

_F_u_n_c_t_i_o_n _t_o _p_l_o_t _c_o_r_r_e_l_a_t_i_o_n _o_f _d_i_f_f_e_r_e_n_t _s_a_m_p_l_e_s

_D_e_s_c_r_i_p_t_i_o_n:

     This function can be used to visualize the (rank) correlation in
     expression data between different samples or sample groups.

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

     corPlot(eset, samples = NULL, grouping = NULL, ref = NULL,...)

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

    eset: object of class 'ExpressionSet' holding the array data, or a
          numeric matrix instead

 samples: which samples' expression shall be correlated to each other;
          either a numeric vector of sample numbers in the
          'ExpressionSet' or a character vector that must be contained
          in the 'sampleNames' of the 'ExpressionSet', default 'NULL'
          means take all samples in the 'ExpressionSet'

grouping: an optional factor vector defining if the correlation should
          be assessed between groups of samples, rather than individual
          samples. If two or more samples are assigned into the same
          group, the mean over these samples' expression values is
          taken before computing correlation. Default NULL means assess
          correlation between individual samples only.

     ref: reference than only applies if argument 'grouping' is given;
          see 'relevel'

     ...: additional arguments, not used yet

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

     No useful return. The function is called for its side-effect to
     produce the pairs plot.

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

     Joern Toedling

_S_e_e _A_l_s_o:

     'ExpressionSet','relevel','pairs'

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

        data(sample.ExpressionSet)
        corPlot(sample.ExpressionSet,
         grouping=paste(sample.ExpressionSet$sex,
         sample.ExpressionSet$type, sep="."))

