plot-methods            package:Rtreemix            R Documentation

_M_e_t_h_o_d _f_o_r _v_i_s_u_a_l_i_z_i_n_g _m_u_t_a_g_e_n_e_t_i_c _t_r_e_e_s _m_i_x_t_u_r_e _m_o_d_e_l_s

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

     Function for visualizing the tree components comprising a
     mutagenetic trees mixture model.   The user can also specify the
     'fontSize' used for the text labels of the nodes and the edges of
     the plotted trees.  Additionally, one can use the parameter 'k' to
     plot a certain tree component from the  mixture model.

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

     ## S4 method for signature 'RtreemixModel, missing':
     plot(x, y, ...)

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

       x: An 'RtreemixModel' object giving the mixture model that
          should be visualized.

       y: Not specified.

     ...: 'fontSize' is the size of the text labels of the nodes and
          the edges of the tree components. The default value is 8. 'k'
          is a 'numeric' giving the specific tree component from the
          given mixture model that should be plotted. Its value  can be
          from one to the number of tree components in the given model. 

_D_e_t_a_i_l_s:

     The value of 'k' (that gives the tree component to be plotted) can
     take '"integer"' values from one to the number of tree components.

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

     The method returns a plot of the mixture model model.

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

     Jasmina Bogojeska

_R_e_f_e_r_e_n_c_e_s:

     Learning multiple evolutionary pathways from cross-sectional data,
     N. Beerenwinkel et al.

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

     'RtreemixData-class', 'RtreemixModel-class', 'generate-methods'

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

     ## Generate a random RtreemixModel object.
     rand.mod <- generate(K = 2, no.events = 7, noise.tree = TRUE, prob = c(0.2, 0.8))

     ## Visualize it.
     plot(rand.mod)

     ## Increase the font size of the text labels in the plot.
     plot(rand.mod, fontSize = 10)

     ## Plot the second component of the mixture model rand.mod
     plot(rand.mod, k = 2)

