comparison kaks_analysis_barplot.R @ 0:844acb833219 draft

Uploaded

0:844acb833219

#!/usr/bin/env Rscript

suppressPackageStartupMessages(library("optparse"))

option_list <- list(
    make_option(c("-c", "--components"), action="store", dest="components", help="Ks significant components input dataset"),
    make_option(c("-o", "--output"), action="store", dest="output", default=NULL, help="Output dataset"),
)

parser <- OptionParser(usage="%prog [options] file", option_list=option_list)
args <- parse_args(parser, positional_arguments=TRUE)
opt <- args$options


get_num_components=function(components_dataset)
{
    # Read in the components data.
    components_data <- read.delim(components_dataset, header=TRUE);
    # Get the max of the number_comp column.
    num_components <- max(components_data[3, ], na.rm=TRUE);
    return = c(components_data, num_components)
    return
}

get_pi_mu_var = function(components_data, num_components) {
    # FixMe: enhance this to generically handle any integer value for num_components.
    if (num_components == 1) {
        pi <- c(components_data[1, 9]);
        mu <- c(components_data[1, 7]);
        var <- c(components_data[1, 8]);
    } else if (num_components == 2) {
        pi <- c(components_data[2, 9], components_data[3, 9]);
        mu <- c(components_data[2, 7], components_data[3, 7]);
        var <- c(components_data[2, 8], components_data[3, 8]);
    } else if (num_components == 3) {
        pi <- c(components_data[4, 9], components_data[5, 9], components_data[6, 9]);
        mu <- c(components_data[4, 7], components_data[5, 7], components_data[6, 7]);
        var <- c(components_data[4, 8], components_data[5, 8], components_data[6, 8]);
    } else if (num_components == 4) {
        pi <- c(components_data[7, 9], components_data[8, 9], components_data[9, 9], components_data[10, 9]);
        mu <- c(components_data[7, 7], components_data[8, 7], components_data[9, 7], components_data[10, 7]);
        var <- c(components_data[7, 8], components_data[8, 8], components_data[9, 8], components_data[10, 8]);
    return = c(pi, mu, var)
    return
}

plot_ks<-function(ksfile, pi, mu, var) {
	#change bin width
	bin <- 0.05 * seq(0, 40);
	kaks <- read.table(file=ksfile, header=T);
	kaks <- kaks[kaks$Ks<2,];
	h.kst <- hist(kaks$Ks, breaks=bin, plot=F);
	nc <- h.kst$counts;
	vx <- h.kst$mids;
	ntot <- sum(nc);
	# Set margin for plot bottom, left top, right.
	par(mai=c(0.5, 0.5, 0, 0));
	# Plot dimension in inches.
	par(pin=c(2.5, 2.5));
	g <- calculate_fitted_density(pi, mu, var);
	h <- ntot * 2.5 / sum(g);
	vx <- seq(1, 100) * 0.02;
	ymax <- max(nc) + 5;
	barplot(nc, space=0.25, offset=0, width=0.04, xlim=c(0,2), ylim=c(0, ymax));
	# Add x-axis.
	axis(1);
	color <- c('green', 'blue', 'black', 'red');
	for (i in 1:length(mu)) {
	   lines(vx, g[,i] * h, lwd=2, col=color[i]);
	}
};

calculate_fitted_density <- function(pi, mu, var) {
	comp <- length(pi);
	var <- var/mu^2;
	mu <- log(mu);;
	#calculate lognormal density
	vx <- seq(1, 100) * 0.02;
	fx <- matrix(0, 100, comp);
	for (i in 1:100) {
	    for (j in 1:comp) {
	       fx[i, j] <- pi[j] * dlnorm(vx[i], meanlog=mu[j], sdlog=(sqrt(var[j])));
	    };
	 };
	fx;
}

# Read in the components data and get the number of components.
items <- get_num_components(opt$components)
components_data <- items[1]
num_components <- items[2]

# Set output file name.
if (is.null(opt$output)) {
    # Name the output file based on the name of the
    # input file, properly handling full path if passed.
    input_filename = basename(opt$components)
    items = strsplit(input_filename, ".")
    output_filename <- paste(items[1], ".components.", num_components, ".pdf")
} else {
    output_filename <- opt$output
}

# Set pi, mu, var.
items <- get_pi_mu_var(components_data, num_components)
pi <- items[1]
mu <- items[2]
var <- items[3]

# Plot the output.
plot_ks(output_filename, pi, mu, var)