meanSdPlot                package:vsn                R Documentation

_P_l_o_t _r_o_w _s_t_a_n_d_a_r_d _d_e_v_i_a_t_i_o_n_s _v_e_r_s_u_s _r_o_w _m_e_a_n_s

_D_e_s_c_r_i_p_t_i_o_n:

     Methods for objects of classes 'matrix',  'ExpressionSet' and
     'vsn' to plot row standard deviations versus row means.

_U_s_a_g_e:

     meanSdPlot(x, 
                ranks = TRUE,
                xlab  = ifelse(ranks, "rank(mean)", "mean"),
                ylab  = "sd",
                pch   = ".",
                plot  = TRUE,
                ...)

_A_r_g_u_m_e_n_t_s:

       x: An object of class 'matrix',  'ExpressionSet', or 'vsn'.

   ranks: Logical, indicating whether the x-axis (means) should be
          plotted on the original scale ('FALSE') or on the rank scale
          ('TRUE'). The latter distributes the data more evenly along
          the x-axis and allows a better visual assessment of the
          standard deviation as a function of  the mean.

    xlab: Character, label for the x-axis.

    ylab: Character, label for the y-axis.

     pch: Plot symbol.

    plot: Logical.  If 'TRUE' (default), a plot is produced. Calling
          the function with 'plot=FALSE' can be useful if only its
          return value is of interest.

     ...: Further arguments that get passed to plot.default.

_D_e_t_a_i_l_s:

     Standard deviation and mean are calculated row-wise from the
     expression matrix (in) 'x'. The scatterplot of these versus each
     other allows to visually verify whether there is a dependence of
     the standard deviation (or variance) on the mean. The red dots
     depict the running median estimator (window-width 10%). If there
     is no variance-mean dependence, then the line formed by the red
     dots should be approximately horizontal.

_V_a_l_u_e:

     A named list with two components, containing x-positions and
     values of the running median estimator (the red dots in the plot).
     The methods can also have a side effect, which is to create a plot
     on the active graphics device.

_A_u_t_h_o_r(_s):

     Wolfgang Huber <URL: http://www.ebi.ac.uk/huber>

_S_e_e _A_l_s_o:

     'vsn'

_E_x_a_m_p_l_e_s:

       data(kidney)
       log.na = function(x) log(ifelse(x>0, x, NA))

       exprs(kidney) = log.na(exprs(kidney))
       meanSdPlot(kidney)

       ## ...try this out with non-logged data, the lymphoma data, your data...

