qtlPlot             package:MetaNetwork             R Documentation

_P_l_o_t _Q_T_L _p_r_o_f_i_l_e_s

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

     Plot QTL profiles.

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

     qtlPlot(markers, qtlProfiles, qtlThres, addTitle=NULL, addMarkerLabels=F, 
             addLegend=T, color=NULL)

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

     Draws a plots that visualizes the -log_{10}(p) QTL values (y-axis)
      along the markers on the genome (x-axis), parameterized based on
     user-defined settings.

_N_o_t_e:

     The 'markers' should be ordered sequentially.  The names of makers
     should be consistent over 'markers' and 'qtlProfiles'.

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

     Jingyuan Fu <j.fu@rug.nl>,  Morris Swertz <m.a.swertz@rug.nl>, 
     Ritsert Jansen <r.c.jansen@rug.nl>

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

     Fu J, Swertz MA, Keurentjes JJB, Jansen RC. MetaNetwork: a
     computational tool for the  genetic study of metabolism. Nature
     Protocols (2007). 

     <URL: http://gbic.biol.rug.nl/supplementary/2007/MetaNetwork>

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

     ## load the example data provided with this package                     
     data(markers)   
     data(genotypes)
     data(traits)                                                       
                                                  
     ##OR: load your own data                     
     #markers    <- loadData("markers.csv")
     #genotypes  <- loadData("genotypes.csv")
     #traits     <- loadData("traits.csv")  
                                                  
     ##calculate the two part qtl
     qtlProfiles <- qtlMapTwoPart(genotypes=genotypes, traits=traits, spike=4)

     ##set the qtl threshold
     qtlThres    <- 3.79

     ##OR: estimate the threshold yourself
     #qtlThres   <- qtlThreshold(genotypes, traits, spike=4)
                                                                                                                            
     ##plot the qtlProfiles
     qtlPlot(markers, qtlProfiles, qtlThres)

