effectplot                package:qtl                R Documentation

_P_l_o_t _p_h_e_n_o_t_y_p_e _m_e_a_n_s _a_g_a_i_n_s_t _g_e_n_o_t_y_p_e_s _a_t _o_n_e _o_r _t_w_o _m_a_r_k_e_r_s.

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

     Plot the phenotype means for each group defined by the genotypes
     at  one or two markers (or the values at a discrete covariate).

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

     effectplot(cross, pheno.col=1, mname1, mark1, geno1, mname2, mark2,
                geno2, main, ylim, add.legend=TRUE)

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

   cross: An object of class 'cross'.

pheno.col: Column number in the phenotype matrix which to be drawn in
          the plot.

  mname1: Name for the first marker.

   mark1: Genotype data for the first marker.  If unspecified,
          genotypes will be taken from the data in the input cross
          object, using the name specified in 'mname1'.

   geno1: Names for the genotypes (or classes in a covariate).

  mname2: Name for the second marker (optional).

   mark2: Like 'mark1' (optional).

   geno2: Names for the genotypes (or classes in a covariate).

    main: Optional figure title.

    ylim: Y-axis limits.

add.legend: A logical value to indicate add legend or not.

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

     In the plot, the Y-axis is the phenotype. X-axis is the genotype
     for the first marker.  In the case of one marker, there will be
     one line in the figure. In the case of two markers, the x-axis is
     for different genotypes of the second marker, and the first marker
     is represented by lines in different colors.  Error bars are
     plotted at +/- 1 SE.

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

     A data.frame containing the phenotype means and standard
     deviations for each group.

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

     Hao Wu, hao@jax.org; Karl W Broman, kbroman@jhsph.edu

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

     'plot.pxg', 'find.marker', 'effectscan'

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

     data(fake.f2)

     # plot of genotype-specific phenotype means for 1 marker
     mname <- find.marker(fake.f2, 1, 37) # marker D1M437
     effectplot(fake.f2, pheno.col=1, mname1=mname)

     # Plot of sex-specific phenotype means
     sex <- fake.f2$pheno[,2]
     effectplot(fake.f2, mname1="Sex", mark1=sex, geno1=c("F","M"))

     # plot of genotype-specific phenotype means for 2 markers
     mname1 <- find.marker(fake.f2, 1, 37) # marker D1M437
     mname2 <- find.marker(fake.f2, 13, 24) # marker D13M254
     effectplot(fake.f2, mname1=mname1, mname2=mname2)

     # Plot of sex- and genotype-specific phenotype means 
     mname <- find.marker(fake.f2, 13, 24) # marker D13M254
     effectplot(fake.f2, mname1=mname, mname2="Sex",
                mark2=fake.f2$pheno$sex, geno2=c("F","M"))

     # Same as above, switch role of sex and the marker
     effectplot(fake.f2, mname1="Sex", mark1=fake.f2$pheno$sex,
                geno1=c("F","M"), mname2=mname)

     # X chromosome marker
     mname <- find.marker(fake.f2, "X", 14) # marker DXM66
     effectplot(fake.f2, mname1=mname)

     # Two markers, including one on the X
     mname1 <- find.marker(fake.f2, 13, 24) # marker D13M254
     mname2 <- find.marker(fake.f2, "X", 14) # marker DXM66
     effectplot(fake.f2, mname1=mname1, mname2=mname2)

