venn                  package:limma                  R Documentation

_V_e_n_n _D_i_a_g_r_a_m_s

_D_e_s_c_r_i_p_t_i_o_n:

     Compute classification counts or plot classification counts in a
     Venn diagram.

_U_s_a_g_e:

     vennCounts(x, include="both")
     vennDiagram(object, include="both", names, mar=rep(1,4), cex=1.5, lwd=1,
     circle.col, counts.col, show.include, ...)

_A_r_g_u_m_e_n_t_s:

       x: numeric matrix of 0's and 1's indicating significance of a
          test. Usually created by 'decideTests'.

  object: either a 'TestResults' matrix or a 'VennCounts' object
          produced by 'vennCounts'.

 include: character string specifying whether to counts genes
          up-regulated, down-regulated or both. See details. Choices
          are '"both"', '"up"' or '"down"'.

   names: optional character vector giving names for the sets or
          contrasts

     mar: numeric vector of length 4 specifying the width of the
          margins around the plot. This argument is passed to 'par'.

     cex: numerical value giving the amount by which the contrast names
          should be scaled on the plot relative to the default.plotting
          text. See 'par'.

     lwd: numerical value giving the amount by which the circles should
          be scaled on the plot. See 'par'.

circle.col: optional vector of color specifications defining the colors
          by which the circles should be drawn. See 'par'.

counts.col: optional vector of color specifications defining the colors
          by which the circles should be drawn. See 'par'.

show.include: logical value whether the value of 'include' should be
          printed on the plot. Defaults to 'FALSE' if 'include' is a
          single value and 'TRUE' otherwise

     ...: any other arguments are passed to 'plot'

_D_e_t_a_i_l_s:

     If a 'vennCounts' object is given to 'vennDiagram', the 'include'
     parameter is ignored. If a 'TestResults' object is given, then it
     is possible to set 'include' as a vector of 2 character strings
     and both will be shown.

_V_a_l_u_e:

     'vennCounts' produces a 'VennCounts' object, which is a numeric
     matrix with last column '"Counts"' giving counts for each possible
     vector outcome. 'vennDiagram' causes a plot to be produced on the
     current graphical device. For 'venDiagram', the number of columns
     of 'object' should be three or fewer.

_A_u_t_h_o_r(_s):

     Gordon Smyth James Wettenhall and Francois Pepin

_S_e_e _A_l_s_o:

     An overview of linear model functions in limma is given by
     06.LinearModels.

_E_x_a_m_p_l_e_s:

     Y <- matrix(rnorm(100*6),100,6)
     Y[1:10,3:4] <- Y[1:10,3:4]+3
     Y[1:20,5:6] <- Y[1:20,5:6]+3
     design <- cbind(1,c(0,0,1,1,0,0),c(0,0,0,0,1,1))
     fit <- eBayes(lmFit(Y,design))
     results <- decideTests(fit)
     a <- vennCounts(results)
     print(a)
     vennDiagram(a)
     vennDiagram(results,include=c("up","down"),counts.col=c("red","green"))