# A plotting R script produced by the REVIGO server at http://revigo.irb.hr/ # If you found REVIGO useful in your work, please cite the following reference: # Supek F et al. "REVIGO summarizes and visualizes long lists of Gene Ontology # terms" PLoS ONE 2011. doi:10.1371/journal.pone.0021800 # -------------------------------------------------------------------------- # If you don't have the ggplot2 package installed, uncomment the following line: # install.packages( "ggplot2" ); library( ggplot2 ); # -------------------------------------------------------------------------- # If you don't have the scales package installed, uncomment the following line: # install.packages( "scales" ); library( scales ); # -------------------------------------------------------------------------- # Here is your data from REVIGO. Scroll down for plot configuration options. revigo.names <- c("term_ID","description","frequency_%","plot_X","plot_Y","plot_size","log10_p_value","uniqueness","dispensability"); revigo.data <- rbind(c("GO:0005976","polysaccharide metabolic process", 1.063,-4.931, 2.793, 5.299,-1.2476,0.811,0.000), c("GO:0050905","neuromuscular process", 0.012, 4.654, 3.710, 3.335,-2.1445,0.412,0.000), c("GO:0007043","cell-cell junction assembly", 0.006, 1.353,-5.931, 3.033,-1.5083,0.486,0.107), c("GO:0048729","tissue morphogenesis", 0.074, 6.241,-0.895, 4.140,-1.3793,0.433,0.124), c("GO:0001508","regulation of action potential", 0.017,-1.656,-3.316, 3.509,-1.3082,0.453,0.134), c("GO:0034330","cell junction organization", 0.018, 2.764,-5.216, 3.516,-1.1538,0.581,0.330), c("GO:0010001","glial cell differentiation", 0.017, 4.624, 1.107, 3.499,-1.1538,0.310,0.532), c("GO:0050885","neuromuscular process controlling balance", 0.007, 4.242, 4.263, 3.104,-1.5083,0.422,0.589), c("GO:0005996","monosaccharide metabolic process", 1.666,-4.527, 3.695, 5.495,-1.1885,0.812,0.598), c("GO:0048598","embryonic morphogenesis", 0.077, 5.226, 1.768, 4.157,-1.1009,0.318,0.631)); one.data <- data.frame(revigo.data); names(one.data) <- revigo.names; one.data <- one.data [(one.data$plot_X != "null" & one.data$plot_Y != "null"), ]; one.data$plot_X <- as.numeric( as.character(one.data$plot_X) ); one.data$plot_Y <- as.numeric( as.character(one.data$plot_Y) ); one.data$plot_size <- as.numeric( as.character(one.data$plot_size) ); one.data$log10_p_value <- as.numeric( as.character(one.data$log10_p_value) ); one.data$frequency <- as.numeric( as.character(one.data$frequency) ); one.data$uniqueness <- as.numeric( as.character(one.data$uniqueness) ); one.data$dispensability <- as.numeric( as.character(one.data$dispensability) ); #head(one.data); # -------------------------------------------------------------------------- # Names of the axes, sizes of the numbers and letters, names of the columns, # etc. can be changed below p1 <- ggplot( data = one.data ); p1 <- p1 + geom_point( aes( plot_X, plot_Y, colour = log10_p_value, size = plot_size), alpha = I(0.6) ) + scale_area(); p1 <- p1 + scale_colour_gradientn( colours = c("blue", "green", "yellow", "red"), limits = c( min(one.data$log10_p_value), 0) ); p1 <- p1 + geom_point( aes(plot_X, plot_Y, size = plot_size), shape = 21, fill = "transparent", colour = I (alpha ("black", 0.6) )) + scale_area(); p1 <- p1 + scale_size( range=c(5, 30)) + theme_bw(); # + scale_fill_gradientn(colours = heat_hcl(7), limits = c(-300, 0) ); ex <- one.data [ one.data$dispensability < 0.15, ]; p1 <- p1 + geom_text( data = ex, aes(plot_X, plot_Y, label = description), colour = I(alpha("black", 0.85)), size = 3 ); p1 <- p1 + labs (y = "semantic space x", x = "semantic space y"); p1 <- p1 + opts(legend.key = theme_blank()) ; one.x_range = max(one.data$plot_X) - min(one.data$plot_X); one.y_range = max(one.data$plot_Y) - min(one.data$plot_Y); p1 <- p1 + xlim(min(one.data$plot_X)-one.x_range/10,max(one.data$plot_X)+one.x_range/10); p1 <- p1 + ylim(min(one.data$plot_Y)-one.y_range/10,max(one.data$plot_Y)+one.y_range/10); # -------------------------------------------------------------------------- # Output the plot to screen p1; # Uncomment the line below to also save the plot to a file. # The file type depends on the extension (default=pdf). # ggsave("C:/Users/path_to_your_file/revigo-plot.pdf");