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1 #!/usr/bin/env Rscript
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2
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3 suppressPackageStartupMessages(library("optparse"))
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4
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5 option_list <- list(
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6 make_option(c("-c", "--components_input"), action="store", dest="components_input", help="Ks significant components input dataset"),
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7 make_option(c("-k", "--kaks_input"), action="store", dest="kaks_input", help="KaKs analysis input dataset"),
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8 make_option(c("-o", "--output"), action="store", dest="output", help="Output dataset")
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9 )
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10
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11 parser <- OptionParser(usage="%prog [options] file", option_list=option_list)
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12 args <- parse_args(parser, positional_arguments=TRUE)
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13 opt <- args$options
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14
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15
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16 get_num_components = function(components_data)
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17 {
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18 # Get the max of the number_comp column.
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19 number_comp = components_data[, 3]
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20 num_components <- max(number_comp, na.rm=TRUE);
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21 num_components
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22 }
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23
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24 get_pi_mu_var = function(components_data, num_components)
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25 {
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26 # FixMe: enhance this to generically handle any integer value for num_components.
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27 if (num_components == 1)
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28 {
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29 pi <- c(components_data[1, 9]);
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30 mu <- c(components_data[1, 7]);
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31 var <- c(components_data[1, 8]);
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32 }
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33 else if (num_components == 2)
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34 {
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35 pi <- c(components_data[2, 9], components_data[3, 9]);
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36 mu <- c(components_data[2, 7], components_data[3, 7]);
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37 var <- c(components_data[2, 8], components_data[3, 8]);
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38 }
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39 else if (num_components == 3)
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40 {
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41 pi <- c(components_data[4, 9], components_data[5, 9], components_data[6, 9]);
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42 mu <- c(components_data[4, 7], components_data[5, 7], components_data[6, 7]);
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43 var <- c(components_data[4, 8], components_data[5, 8], components_data[6, 8]);
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44 }
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45 else if (num_components == 4)
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46 {
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47 pi <- c(components_data[7, 9], components_data[8, 9], components_data[9, 9], components_data[10, 9]);
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48 mu <- c(components_data[7, 7], components_data[8, 7], components_data[9, 7], components_data[10, 7]);
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49 var <- c(components_data[7, 8], components_data[8, 8], components_data[9, 8], components_data[10, 8]);
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50 }
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51 return = c(pi, mu, var)
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52 return
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53 }
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54
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55 plot_ks<-function(kaks_input, output, pi, mu, var)
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56 {
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57 # Start PDF device driver to save charts to output.
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58 pdf(file=output, bg="white")
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59 # Change bin width
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60 bin <- 0.05 * seq(0, 40);
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61 kaks <- read.table(file=kaks_input, header=T);
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62 kaks <- kaks[kaks$Ks<2,];
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63 h.kst <- hist(kaks$Ks, breaks=bin, plot=F);
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64 nc <- h.kst$counts;
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65 vx <- h.kst$mids;
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66 ntot <- sum(nc);
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67 # Set margin for plot bottom, left top, right.
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68 par(mai=c(0.5, 0.5, 0, 0));
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69 # Plot dimension in inches.
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70 par(pin=c(2.5, 2.5));
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71 g <- calculate_fitted_density(pi, mu, var);
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72 h <- ntot * 2.5 / sum(g);
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73 vx <- seq(1, 100) * 0.02;
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74 ymax <- max(nc) + 5;
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75 barplot(nc, space=0.25, offset=0, width=0.04, xlim=c(0,2), ylim=c(0, ymax));
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76 # Add x-axis.
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77 axis(1);
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78 color <- c('green', 'blue', 'black', 'red');
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79 for (i in 1:length(mu))
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80 {
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81 lines(vx, g[,i] * h, lwd=2, col=color[i]);
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82 }
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83 };
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84
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85 calculate_fitted_density <- function(pi, mu, var)
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86 {
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87 comp <- length(pi);
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88 var <- var/mu^2;
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89 mu <- log(mu);
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90 #calculate lognormal density
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91 vx <- seq(1, 100) * 0.02;
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92 fx <- matrix(0, 100, comp);
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93 for (i in 1:100)
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94 {
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95 for (j in 1:comp)
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96 {
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97 fx[i, j] <- pi[j] * dlnorm(vx[i], meanlog=mu[j], sdlog=(sqrt(var[j])));
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98 };
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99 };
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100 fx;
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101 }
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102
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103 # Read in the components data.
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104 components_data <- read.delim(opt$components_input, header=TRUE);
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105 # Get the number of components.
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106 num_components <- get_num_components(components_data)
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107
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108 # Set pi, mu, var.
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109 items <- get_pi_mu_var(components_data, num_components);
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110 pi <- items[1];
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111 mu <- items[2];
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112 var <- items[3];
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113
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114 # Plot the output.
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115 plot_ks(opt$kaks_input, opt$output, pi, mu, var);
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