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, xlab, ylab, col, add.legend=TRUE,
                legend.lab, draw=TRUE, var.flag=c("pooled","group"))

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

   cross: An object of class 'cross'.

pheno.col: Column number in the phenotype matrix to be drawn in the
          plot.  One may also give a character string matching a
          phenotype name. Finally, one may give a numeric vector of
          phenotypes, in which case it must have the length equal to
          the number of individuals in the cross, and there must be
          either non-integers or values < 1 or > no. phenotypes; this
          last case may be useful for studying transformations.

  mname1: Name for the first marker or pseudomarker. Pseudomarkers
          (that is, non-marker positions on the imputation grid) may be
          referred to in a form like '"5@30.3"', for position 30.3 on
          chromosome 5.

   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: Optional labels for the genotypes (or classes in a
          covariate).

  mname2: Name for the second marker or pseudomarker (optional).

   mark2: Like 'mark1' (optional).

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

    main: Optional figure title.

    ylim: Optional y-axis limits.

    xlab: Optional x-axis label.

    ylab: Optional y-axis label.

     col: Optional vector of colors for the different line segments.

add.legend: A logical value to indicate whether to add a legend.

legend.lab: Optional title for the legend.

    draw: A logical value to indicate generate the plot or not. If
          FALSE, no figure will be plotted and this function can be
          used to calculate the group means and standard errors.

var.flag: The method to calculate the group variance. "pooled" means to
          use the pooled variance and "group" means to calculate from
          individual group.

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

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

     The results of 'sim.geno' are used; if they are not available,
     'sim.geno' is run with 'n.draws=16'.  The average phenotype for
     each genotype group takes account of missing genotype data by
     averaging across the imputations.  The SEs take account of both
     the residual phenotype variation and the imputation error.

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

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

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

     Hao Wu; Karl W Broman, kbroman@biostat.wisc.edu

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

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

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

     data(fake.f2)


     # impute genotype data
     ## Not run: 
     fake.f2 <- sim.geno(fake.f2, step=5, n.draws=64)
     ## End(Not run)

     ########################################
     # one marker plots
     ########################################
     ### 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 a phenotype
     # Plot of sex-specific phenotype means,
     # note that "sex" must be a phenotype name here
     effectplot(fake.f2, mname1="sex", geno1=c("F","M"))
     # alternatively:
     sex <- pull.pheno(fake.f2, "sex")
     effectplot(fake.f2, mname1="Sex", mark1=sex, geno1=c("F","M"))

     ########################################
     # two markers plots
     ########################################

     ### plot two markers
     # 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 two pseudomarkers
     #####  refer to pseudomarkers by their positions
     effectplot(fake.f2, mname1="1@35", mname2="13@25")

     #####  alternatively, find their names via find.pseudomarker
     pmnames <- find.pseudomarker(fake.f2, chr=c(1, 13), c(35, 25))
     effectplot(fake.f2, mname1=pmnames[1], mname2=pmnames[2])

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

     # Same as above, switch role of sex and the marker
     # sex and marker
     effectplot(fake.f2, mname1="Sex", mark1=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
     mnames <- find.marker(fake.f2, c(13, "X"), c(24, 14))
     effectplot(fake.f2, mname1=mnames[1], mname2=mnames[2])

