Mercurial > repos > artbio > mutational_patterns

comparison mutational_patterns.R @ 17:8c6ee1c2248f draft

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"planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/mutational_patterns commit e5d498dfc5a6a9aaea3d09037dea5d15c2d85dd2"
author artbio
date Tue, 05 Oct 2021 22:28:34 +0000
parents 31e7a33ecd71
children 8d9f31389f33
comparison
equal deleted inserted replaced
16:31e7a33ecd71 17:8c6ee1c2248f
95 ), 95 ),
96 make_option( 96 make_option(
97 c("-r", "--rdata"), 97 c("-r", "--rdata"),
98 type = "character", 98 type = "character",
99 default = NULL, 99 default = NULL,
100 help = "Path to RData output file") 100 help = "Path to RData output file"
101 ),
102 make_option(
103 c("-t", "--tooldir"),
104 type = "character",
105 default = NULL,
106 help = "Path to tool directory, where tool data are stored")
107
101 ) 108 )
102 109
103 opt <- parse_args(OptionParser(option_list = option_list), 110 opt <- parse_args(OptionParser(option_list = option_list),
104 args = commandArgs(trailingOnly = TRUE)) 111 args = commandArgs(trailingOnly = TRUE))
105 112
215 dev.off() 222 dev.off()
216 } 223 }
217 ##### Section 3: Find optimal contribution of known signatures: COSMIC mutational signatures #### 224 ##### Section 3: Find optimal contribution of known signatures: COSMIC mutational signatures ####
218 225
219 if (!is.na(opt$output_cosmic)[1]) { 226 if (!is.na(opt$output_cosmic)[1]) {
227 # Prepare cosmic signatures
228 cosmic_urls <- read.delim(paste0(opt$tooldir, "cosmic_urls.tsv"), sep = "\t", header = TRUE)
229 cosmic_sbs_file <- cosmic_urls$url[cosmic_urls$genome == opt$genome &
230 cosmic_urls$cosmic_version == opt$cosmic_version]
231 cancer_sbs_signatures <- read.table(paste0(opt$tooldir, cosmic_sbs_file),
232 sep = "\t", header = TRUE)
233 row.names(cancer_sbs_signatures) <- cancer_sbs_signatures$Type
234 new_order <- match(row.names(mut_mat), cancer_sbs_signatures$Type)
235 cancer_sbs_signatures <- cancer_sbs_signatures[as.numeric(new_order), ]
236 cosmic_tag <- paste(opt$genome, "COSMIC", opt$cosmic_version, sep = " ")
237 cosmic_colors <- col_vector[seq_len(ncol(cancer_sbs_signatures) - 1)]
238 names(cosmic_colors) <- colnames(cancer_sbs_signatures[2:length(cancer_sbs_signatures)])
239 cancer_sbs_matrix <- as.matrix(cancer_sbs_signatures[, 2:length(cancer_sbs_signatures)])
240
241
242 # Plot mutational profiles of the COSMIC signatures
220 pdf(opt$output_cosmic, paper = "special", width = 11.69, height = 11.69) 243 pdf(opt$output_cosmic, paper = "special", width = 11.69, height = 11.69)
221 pseudo_mut_mat <- mut_mat + 0.0001 # First add a small psuedocount to the mutation count matrix
222 if (opt$cosmic_version == "v2") { 244 if (opt$cosmic_version == "v2") {
223 sp_url <- "https://cancer.sanger.ac.uk/signatures/documents/420/COSMIC_v2_SBS_GRCh38.txt" 245 p6 <- plot_96_profile(cancer_sbs_matrix, condensed = TRUE, ymax = 0.3)
224 cancer_signatures <- read.table(sp_url, sep = "\t", header = TRUE) 246 grid.arrange(p6, top = textGrob("COSMIC SBS signature profiles", gp = gpar(fontsize = 12, font = 3)))
225 new_order <- match(row.names(pseudo_mut_mat), cancer_signatures$Type)
226 cancer_signatures <- cancer_signatures[as.vector(new_order), ]
227 row.names(cancer_signatures) <- cancer_signatures$Type
228 cancer_signatures <- as.matrix(cancer_signatures[, 2:31])
229 colnames(cancer_signatures) <- gsub("Signature_", "", colnames(cancer_signatures)) # shorten signature labels
230 cosmic_tag <- "Signatures (Cosmic v2, March 2015)"
231 cosmic_colors <- col_vector[1:30]
232 names(cosmic_colors) <- colnames(cancer_signatures)
233 } else {
234 sp_url <- "https://cancer.sanger.ac.uk/signatures/documents/431/COSMIC_v3_SBS_GRCh38.txt"
235 cancer_signatures <- read.table(sp_url, sep = "\t", header = TRUE)
236 new_order <- match(row.names(pseudo_mut_mat), cancer_signatures$Type)
237 cancer_signatures <- cancer_signatures[as.vector(new_order), ]
238 row.names(cancer_signatures) <- cancer_signatures$Type
239 cancer_signatures <- as.matrix(cancer_signatures[, 2:68])
240 colnames(cancer_signatures) <- gsub("SBS", "", colnames(cancer_signatures)) # shorten signature labels
241 cosmic_tag <- "Signatures (Cosmic v3, May 2019)"
242 cosmic_colors <- col_vector[1:67]
243 names(cosmic_colors) <- colnames(cancer_signatures)
244 }
245
246 # Plot mutational profiles of the COSMIC signatures
247 if (opt$cosmic_version == "v2") {
248 p6 <- plot_96_profile(cancer_signatures, condensed = TRUE, ymax = 0.3)
249 grid.arrange(p6, top = textGrob("COSMIC signature profiles", gp = gpar(fontsize = 12, font = 3)))
250 } else { 247 } else {
251 p6 <- plot_96_profile(cancer_signatures[, 1:33], condensed = TRUE, ymax = 0.3) 248 p6 <- plot_96_profile(cancer_sbs_matrix[, 1:trunc(ncol(cancer_sbs_matrix) / 2)], condensed = TRUE, ymax = 0.3)
252 p6bis <- plot_96_profile(cancer_signatures[, 34:67], condensed = TRUE, ymax = 0.3) 249 p6bis <- plot_96_profile(cancer_sbs_matrix[, (trunc(ncol(cancer_sbs_matrix) / 2) + 1):ncol(cancer_sbs_matrix)],
250 condensed = TRUE, ymax = 0.3)
253 grid.arrange(p6, top = textGrob("COSMIC signature profiles (on two pages)", 251 grid.arrange(p6, top = textGrob("COSMIC signature profiles (on two pages)",
254 gp = gpar(fontsize = 12, font = 3))) 252 gp = gpar(fontsize = 12, font = 3)))
255 grid.arrange(p6bis, top = textGrob("COSMIC signature profiles (continued)", 253 grid.arrange(p6bis, top = textGrob("COSMIC signature profiles (continued)",
256 gp = gpar(fontsize = 12, font = 3))) 254 gp = gpar(fontsize = 12, font = 3)))
257 } 255 }
258 256
259 257
260 # Find optimal contribution of COSMIC signatures to reconstruct 96 mutational profiles 258 # Find optimal contribution of COSMIC signatures to reconstruct 96 mutational profiles
261 fit_res <- fit_to_signatures(pseudo_mut_mat, cancer_signatures) 259 pseudo_mut_mat <- mut_mat + 0.0001 # First add a small pseudocount to the mutation count matrix
260 fit_res <- fit_to_signatures(pseudo_mut_mat, cancer_sbs_matrix)
262 261
263 # Plot contribution barplots 262 # Plot contribution barplots
264 pc3 <- plot_contribution(fit_res$contribution, cancer_signatures, coord_flip = T, mode = "absolute") 263 pc3 <- plot_contribution(fit_res$contribution, cancer_sbs_matrix, coord_flip = T, mode = "absolute")
265 pc4 <- plot_contribution(fit_res$contribution, cancer_signatures, coord_flip = T, mode = "relative") 264 pc4 <- plot_contribution(fit_res$contribution, cancer_sbs_matrix, coord_flip = T, mode = "relative")
266 if (is.na(opt$levels)[1]) { # if there are NO levels to display in graphs 265 if (is.na(opt$levels)[1]) { # if there are NO levels to display in graphs
267 pc3_data <- pc3$data 266 pc3_data <- pc3$data
268 pc3 <- ggplot(pc3_data, aes(x = Sample, y = Contribution, fill = as.factor(Signature))) + 267 pc3 <- ggplot(pc3_data, aes(x = Sample, y = Contribution, fill = as.factor(Signature))) +
269 geom_bar(stat = "identity", position = "stack") + 268 geom_bar(stat = "identity", position = "stack") +
270 coord_flip() + 269 coord_flip() +
372 } 371 }
373 372
374 # export relative contribution matrix 373 # export relative contribution matrix
375 if (!is.na(opt$sig_contrib_matrix)) { 374 if (!is.na(opt$sig_contrib_matrix)) {
376 output_table <- t(fit_res$contribution) / rowSums(t(fit_res$contribution)) 375 output_table <- t(fit_res$contribution) / rowSums(t(fit_res$contribution))
377 colnames(output_table) <- paste0("s", colnames(output_table))
378 if (length(levels(factor(levels_table$level))) > 1) { 376 if (length(levels(factor(levels_table$level))) > 1) {
379 output_table <- data.frame(sample = paste0(metadata_table[metadata_table$element_identifier == colnames(fit_res$contribution), 377 output_table <- data.frame(sample = paste0(metadata_table[metadata_table$element_identifier == colnames(fit_res$contribution),
380 3], "-", colnames(fit_res$contribution)), 378 3], "-", colnames(fit_res$contribution)),
381 output_table) 379 output_table)
382 } else { 380 } else {