library(ape)
library(CommT)
library(ggplot2)
library(gridExtra)
library(phangorn)
library(reshape)
n_genes = 10
n_sims = sprintf("%02d", 1:20)
for (s in n_sims) {
cat(paste("\n", "Analyzing simulation", s, "\n"))
# Keywords: noswap, g1swap, g1a2swap, g1t4swap, gAllShuf
# Specify input file names (User input necessary)
BEAST_prefix = paste("/home/michael_science/Desktop/CommT_Project/Revision_SupplFigure1/05_Project_CommT_Jan2015/03_KFdist_distributions/01_input/01_starBEAST_geneTrees/CommT.Jan2015.g1t4swap.sim.", s, ".gene", sep="")
starBEAST_prefix = paste("/home/michael_science/Desktop/CommT_Project/Revision_SupplFigure1/05_Project_CommT_Jan2015/03_KFdist_distributions/01_input/02_BEAST_GeneTrees/CommT.Jan2015.g1t4swap.sim.", s, ".gene", sep="")
# Load data
post_gt_distrs_BEAST = list()
post_gt_distrs_starBEAST = list()
for (g in 1:n_genes) {
g_lz = sprintf("%03d", g)
post_gt_distrs_BEAST[[g]] = read.nexus(paste(BEAST_prefix, g_lz, ".trees", sep=""))
post_gt_distrs_starBEAST[[g]] = read.nexus(paste(starBEAST_prefix, g_lz, ".trees", sep=""))
}
# Calculate KF distances
in_data = CommT.kfdist(post_gt_distrs_BEAST, post_gt_distrs_starBEAST, outlier_num=c())
# Generate ANOVA legend
legend_text = CommT.anova(in_data)
# Generate coordinates for plot
legend_pos = CommT.legendpos(in_data)
# Visualize KF distances
#my_plot = CommT.viz(in_data, "a_project_name_here", alpha=0.05, legend_text, legend_pos)
my_plot = CommT.viz(in_data, paste("sim.", s, sep=""), alpha=0.05, legend_text, legend_pos)
# Save plot
assign(paste("sim.", s, sep=""), my_plot)
}
# Specify output file names (User input necessary)
svg("/home/michael_science/Desktop/CommT_Project/Revision_SupplFigure1/05_Project_CommT_Jan2015/03_KFdist_distributions/03_original_visualizations_with_Rpackage/05_BEAST.to.starBEAST_KFdist_g1t4swap.svg", width=30, height=26)
grid.arrange(sim.01, sim.02, sim.03, sim.04, sim.05,
sim.06, sim.07, sim.08, sim.09, sim.10,
sim.11, sim.12, sim.13, sim.14, sim.15,
sim.16, sim.17, sim.18, sim.19, sim.20, ncol=5)
dev.off()
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