# HG changeset patch # User greg # Date 1498663217 14400 # Node ID 56f42cc1dd58385e8e64930fc9ceb5a692a6778c # Parent c5846258c458919a75b228393b8a744dfd13b7fe Uploaded diff -r c5846258c458 -r 56f42cc1dd58 components.tabular --- a/components.tabular Thu Jun 08 12:55:49 2017 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,2 +0,0 @@ -species n number_comp lnL AIC BIC mean variance porportion -species1 3 1 -3.4750 6.95 6.95 3.1183 5.7732 1.00 diff -r c5846258c458 -r 56f42cc1dd58 kaks_input1.tabular --- a/kaks_input1.tabular Thu Jun 08 12:55:49 2017 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,4 +0,0 @@ -SEQ1 SEQ2 Ka Ks Ka\Ks -contig_241; contig_241 1.5312 7.1619 0.2138 -contig_300 contig_300; 0.8653 3.7872 0.2285 -contig_586 contig_586; 1.7791 1.1181 1.5912 diff -r c5846258c458 -r 56f42cc1dd58 ks_distribution.R --- a/ks_distribution.R Thu Jun 08 12:55:49 2017 -0400 +++ b/ks_distribution.R Wed Jun 28 11:20:17 2017 -0400 @@ -5,67 +5,86 @@ option_list <- list( make_option(c("-c", "--components_input"), action="store", dest="components_input", help="Ks significant components input dataset"), make_option(c("-k", "--kaks_input"), action="store", dest="kaks_input", help="KaKs analysis input dataset"), - make_option(c("-o", "--output"), action="store", dest="output", help="Output dataset") + make_option(c("-n", "--number_comp"), action="store", dest="number_comp", type="integer", help="Number of significant components in the Ks distribution"), + make_option(c("-o", "--output"), action="store", dest="output", help="Output dataset"), + make_option(c("-s", "--specified_colors"), action="store", dest="specified_colors", default=NULL, help="List of component colors") ) 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_data) -{ - # Get the max of the number_comp column. - number_comp = components_data[, 3] - num_components <- max(number_comp, na.rm=TRUE) - return(num_components) +set_component_colors = function(colors, number_comp) { + # Handle colors for components. + if (is.null(colors)) { + # Randomly specify colors for components. + component_colors <- c("red", "yellow", "green", "black", "blue", "darkorange") + } else { + # Handle selected colors for components. + component_colors <- c() + colors <- as.character(colors) + items <- strsplit(colors, ",") + for (item in items) { + component_colors <- c(component_colors, item) + } + num_colors_specified <- length(component_colors) + if (num_colors_specified < number_comp) { + # The number of selected colors is less than the number of + # components, so we'll add random colors that were not + # selected to the set of component colors until we have a + # color for each component. + loop_count <- number_comp - num_colors_specified + for (i in 1:loop_count) { + if (!(is.element("red", component_colors))) { + component_colors <- c(component_colors, "red") + } else if (!(is.element("yellow", component_colors))) { + component_colors <- c(component_colors, "yellow") + } else if (!(is.element("green", component_colors))) { + component_colors <- c(component_colors, "green") + } else if (!(is.element("black", component_colors))) { + component_colors <- c(component_colors, "black") + } else if (!(is.element("blue", component_colors))) { + component_colors <- c(component_colors, "blue") + } else if (!(is.element("darkorange", component_colors))) { + component_colors <- c(component_colors, "darkorange") + } + } + } + } + return(component_colors) } -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) - { +get_pi_mu_var = function(components_data, number_comp) { + if (number_comp == 1) { pi <- c(components_data[1, 9]) mu <- c(components_data[1, 7]) var <- c(components_data[1, 8]) - } - else if (num_components == 2) - { + } else if (number_comp == 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) - { + } else if (number_comp == 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) - { + } else if (number_comp == 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]) - } - else if (num_components == 5) - { + } else if (number_comp == 5) { pi <- c(components_data[11, 9], components_data[12, 9], components_data[13, 9], components_data[14, 9], components_data[15, 9]) mu <- c(components_data[11, 7], components_data[12, 7], components_data[13, 7], components_data[14, 7], components_data[15, 7]) var <- c(components_data[11, 8], components_data[12, 8], components_data[13, 8], components_data[14, 8], components_data[15, 8]) - } - else if (num_components == 6) - { + } else if (number_comp == 6) { pi <- c(components_data[16, 9], components_data[17, 9], components_data[18, 9], components_data[19, 9], components_data[20, 9], components_data[21, 9]) mu <- c(components_data[16, 7], components_data[17, 7], components_data[18, 7], components_data[19, 7], components_data[20, 7], components_data[21, 7]) var <- c(components_data[16, 8], components_data[17, 8], components_data[18, 8], components_data[19, 8], components_data[20, 8], components_data[21, 8]) } - results = c(pi, mu, var) + results <- c(pi, mu, var) return(results) } -plot_ks<-function(kaks_input, output, pi, mu, var) -{ +plot_ks<-function(kaks_input, component_colors, output, pi, mu, var) { # Start PDF device driver to save charts to output. pdf(file=output, bg="white") kaks <- read.table(file=kaks_input, header=T) @@ -89,27 +108,24 @@ barplot(nc, space=0.25, offset=0, width=0.04, xlim=c(0, max_ks), ylim=c(0, ymax), col="lightpink1", border="lightpink3") # Add x-axis. axis(1) - color <- c('red', 'yellow','green','black','blue', 'darkorange' ) - for (i in 1:length(mu)) - { - lines(vx, g[,i] * h, lwd=2, col=color[i]) + for (i in 1:length(mu)) { + lines(vx, g[,i] * h, lwd=2, col=component_colors[i]) } } -calculate_fitted_density <- function(pi, mu, var, max_ks) -{ +calculate_fitted_density <- function(pi, mu, var, max_ks) { comp <- length(pi) var <- var/mu^2 mu <- log(mu) # Calculate lognormal density. vx <- seq(1, 100) * (max_ks / 100) 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]))) - if (is.nan(fx[i,j])) fx[i,j]<-0 + 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]))) + if (is.nan(fx[i,j])) { + fx[i,j]<-0 + } } } return(fx) @@ -117,47 +133,42 @@ # Read in the components data. components_data <- read.delim(opt$components_input, header=TRUE) -# Get the number of components. -num_components <- get_num_components(components_data) +number_comp <- as.integer(opt$number_comp) +if (number_comp == 0) { + # Default to 1 component to allow functional testing. + number_comp <- 1 +} + +# Set component colors. +component_colors <- set_component_colors(opt$specified_colors, number_comp) # Set pi, mu, var. -items <- get_pi_mu_var(components_data, num_components) -if (num_components == 1) -{ - pi <- items[1] - mu <- items[2] - var <- items[3] -} -if (num_components == 2) -{ - pi <- items[1:2] - mu <- items[3:4] - var <- items[5:6] -} -if (num_components == 3) -{ - pi <- items[1:3] - mu <- items[4:6] - var <- items[7:9] -} -if (num_components == 4) -{ - pi <- items[1:4] - mu <- items[5:8] - var <- items[9:12] -} -if (num_components == 5) -{ - pi <- items[1:5] - mu <- items[6:10] - var <- items[11:15] -} -if (num_components == 6) -{ - pi <- items[1:6] - mu <- items[7:12] - var <- items[13:18] +items <- get_pi_mu_var(components_data, number_comp) +if (number_comp == 1) { + pi <- items[1] + mu <- items[2] + var <- items[3] +} else if (number_comp == 2) { + pi <- items[1:2] + mu <- items[3:4] + var <- items[5:6] +} else if (number_comp == 3) { + pi <- items[1:3] + mu <- items[4:6] + var <- items[7:9] +} else if (number_comp == 4) { + pi <- items[1:4] + mu <- items[5:8] + var <- items[9:12] +} else if (number_comp == 5) { + pi <- items[1:5] + mu <- items[6:10] + var <- items[11:15] +} else if (number_comp == 6) { + pi <- items[1:6] + mu <- items[7:12] + var <- items[13:18] } # Plot the output. -plot_ks(opt$kaks_input, opt$output, pi, mu, var) +plot_ks(opt$kaks_input, component_colors, opt$output, pi, mu, var) diff -r c5846258c458 -r 56f42cc1dd58 ks_distribution.xml --- a/ks_distribution.xml Thu Jun 08 12:55:49 2017 -0400 +++ b/ks_distribution.xml Wed Jun 28 11:20:17 2017 -0400 @@ -1,4 +1,4 @@ - + plots the distribution of synonymous substitution (Ks) rates and fits significant component(s) macros.xml @@ -8,11 +8,39 @@ Rscript $__tool_directory__/ks_distribution.R -k '$input' -c '$components' +-n $components.metadata.number_comp -o '$output' +#if str($choose_colors_cond.choose_colors) == 'yes': + #set specified_colors = list() + #for $selection in $choose_colors_cond.colors: + $specified_colors.append(str($selection.color)) + #end for + #set specified_colors = ",".join($specified_colors) + -s '$specified_colors' +#end if ]]> - + + + + + + + + + + + + + + + + + + + + @@ -20,7 +48,7 @@ - + @@ -37,6 +65,9 @@ * **Synonymous substitution rates** - estimated synonymous substitution (Ks) rates output file produced by the KaKsAnalysis tool selected from your history. * **Synonymous components** - estimated significant component(s) output file produced by the KaKsAnalysis tool selected from your history. + * **Choose colors for significant components** - select 'Yes' to specify component colors or 'No' for colors chosen randlomly. + + * **Component colors** - select a color from the palette for each component (colors will be chosen randomly for unspecified components). diff -r c5846258c458 -r 56f42cc1dd58 macros.xml --- a/macros.xml Thu Jun 08 12:55:49 2017 -0400 +++ b/macros.xml Wed Jun 28 11:20:17 2017 -0400 @@ -3,7 +3,7 @@ 1.0 - plant_tribes_assembly_post_processor + plant_tribes_assembly_post_processor diff -r c5846258c458 -r 56f42cc1dd58 output.pdf --- a/output.pdf Thu Jun 08 12:55:49 2017 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,52 +0,0 @@ -1 0 obj -<< -/Title (R Graphics Output) -/Creator (R) ->> -endobj -2 0 obj -<< /Type /Catalog /Pages 3 0 R >> -endobj -7 0 obj -<< /Type /Page /Parent 3 0 R /Contents 8 0 R /Resources 4 0 R >> -endobj -8 0 obj -<< ->> -stream -endobj -3 0 obj -<< /Type /Pages /Kids [ 7 0 R ] /Count 1 /MediaBox [0 0 504 504] >> -endobj -4 0 obj -<< -/ProcSet [/PDF /Text] -/Font <> -/ExtGState << >> -/ColorSpace << /sRGB 5 0 R >> ->> -endobj -5 0 obj -[/ICCBased 6 0 R] -endobj -6 0 obj -<< /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> -stream -9 0 obj -<< -/Type /Encoding /BaseEncoding /WinAnsiEncoding -/Differences [ 45/minus 96/quoteleft -144/dotlessi /grave /acute /circumflex /tilde /macron /breve /dotaccent -/dieresis /.notdef /ring /cedilla /.notdef /hungarumlaut /ogonek /caron /space] ->> -endobj -10 0 obj -<< /Type /Font /Subtype /Type1 /Name /F2 /BaseFont /Helvetica -/Encoding 9 0 R >> -endobj -xref -0 11 -trailer -<< /Size 11 /Info 1 0 R /Root 2 0 R >> -startxref -%%EOF diff -r c5846258c458 -r 56f42cc1dd58 test-data/components.ptkscmp --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/components.ptkscmp Wed Jun 28 11:20:17 2017 -0400 @@ -0,0 +1,2 @@ +species n number_comp lnL AIC BIC mean variance porportion +species1 3 1 -3.4750 6.95 6.95 3.1183 5.7732 1.00 diff -r c5846258c458 -r 56f42cc1dd58 test-data/kaks_input1.tabular --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/kaks_input1.tabular Wed Jun 28 11:20:17 2017 -0400 @@ -0,0 +1,4 @@ +SEQ1 SEQ2 Ka Ks Ka\Ks +contig_241; contig_241 1.5312 7.1619 0.2138 +contig_300 contig_300; 0.8653 3.7872 0.2285 +contig_586 contig_586; 1.7791 1.1181 1.5912 diff -r c5846258c458 -r 56f42cc1dd58 test-data/output.pdf --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/output.pdf Wed Jun 28 11:20:17 2017 -0400 @@ -0,0 +1,52 @@ +1 0 obj +<< +/Title (R Graphics Output) +/Creator (R) +>> +endobj +2 0 obj +<< /Type /Catalog /Pages 3 0 R >> +endobj +7 0 obj +<< /Type /Page /Parent 3 0 R /Contents 8 0 R /Resources 4 0 R >> +endobj +8 0 obj +<< +>> +stream +endobj +3 0 obj +<< /Type /Pages /Kids [ 7 0 R ] /Count 1 /MediaBox [0 0 504 504] >> +endobj +4 0 obj +<< +/ProcSet [/PDF /Text] +/Font <> +/ExtGState << >> +/ColorSpace << /sRGB 5 0 R >> +>> +endobj +5 0 obj +[/ICCBased 6 0 R] +endobj +6 0 obj +<< /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> +stream +9 0 obj +<< +/Type /Encoding /BaseEncoding /WinAnsiEncoding +/Differences [ 45/minus 96/quoteleft +144/dotlessi /grave /acute /circumflex /tilde /macron /breve /dotaccent +/dieresis /.notdef /ring /cedilla /.notdef /hungarumlaut /ogonek /caron /space] +>> +endobj +10 0 obj +<< /Type /Font /Subtype /Type1 /Name /F2 /BaseFont /Helvetica +/Encoding 9 0 R >> +endobj +xref +0 11 +trailer +<< /Size 11 /Info 1 0 R /Root 2 0 R >> +startxref +%%EOF