Mercurial > repos > iarc > mutspec
view R/somaticSignature_Galaxy.r @ 7:eda59b985b1c draft default tip
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| author | iarc |
|---|---|
| date | Mon, 13 Mar 2017 08:21:19 -0400 |
| parents | 46a10309dfe2 |
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#!/usr/bin/Rscript #-----------------------------------# # Author: Maude # # Script: somaticSignature_Galaxy.r # # Last update: 17/02/17 # #-----------------------------------# ######################################################################################################################################### # Run NMF algorithm and represent the composition of somatic signatures and the contribution in each samples # ######################################################################################################################################### #------------------------------------------------------------------------------- # Load library for recovering the arguments #------------------------------------------------------------------------------- suppressMessages(suppressWarnings(require("getopt"))) #------------------------------------------------------------------------------- # Recover the arguments #------------------------------------------------------------------------------- spec = matrix(c( "input" , "i", 1, "character", "nbSignature", "nbSign", 1, "integer", "cpu", "cpu", 1, "integer", "output", "o", 1, "character", "html", "html", 0, "character", "help", "h", 0, "logical" ), byrow=TRUE, ncol=4 ) opt = getopt(spec); # No argument is pass to the command line if(length(opt) == 1) { cat(paste("Usage:\n somaticSignature_Galaxy.r --input <matrix> --nbSignature <nbSign> --cpu <cpu> --output <outputdir> --html <html_for_Galaxy>\n",sep="")) cat(paste0("\n--input Input matrix created with the tool MutSpec-Stat\n--nbSignature Number of signatures to extract (min = 2)\n--cpu Number of CPUs\n--output Output directory\n--html Path to HTML page (ONLY FOR GALAXY WRAPPER)\n")) q(status=1) } # Help was asked for. if ( !is.null(opt$help) ) { # print a friendly message and exit with a non-zero error code cat(paste("Usage:\n somaticSignature_Galaxy.r --input <matrix> --nbSignature <nbSign> --cpu <cpu> --output <outputdir> --html <html_for_Galaxy>\n",sep="")) q(status=1) } #------------------------------------------------------------------------------- # Load library #------------------------------------------------------------------------------- suppressMessages(suppressWarnings(library(NMF))) suppressMessages(suppressWarnings(library(ggplot2))) suppressMessages(suppressWarnings(library(reshape))) suppressMessages(suppressWarnings(library(grid))) suppressMessages(suppressWarnings(library(scales))) # Set the maximum value to the y axis (graph composition somatic signature) suppressMessages(suppressWarnings(library(gridExtra))) # function "unit" ############################################################################### # Load the functions # ############################################################################### #------------------------------------------------------------------------------- # Set the font depending on X11 availability #------------------------------------------------------------------------------- font <- "" # Check the device available device <- capabilities() # X11 is available if(device[5]) { font <- "Helvetica" } else { font <- "Helvetica-Narrow" } #------------------------------------------------------------------------------- # My own theme #------------------------------------------------------------------------------- theme_custom <- function(base_size = 4, base_family = "") { # Starts with theme_grey and then modify some parts theme_grey(base_size = base_size, base_family = base_family) %+replace% theme( axis.text = element_text(size = rel(0.8), family=font), axis.ticks = element_line(colour = "black", size=.2), axis.line = element_line(colour = "black", size = .2), axis.ticks.length= unit(.05, "cm"), axis.ticks.margin= unit(.05, "cm"), # space between tick mark and tick label (‘unit’) legend.key.size = unit(.2, "cm"), legend.margin = unit(-.5, "cm"), panel.background = element_blank(), panel.border = element_blank(), panel.grid.major = element_blank(), panel.grid.minor = element_blank(), strip.text.y = element_text(size = 3) ) } #------------------------------------------------------------------------------- # Customize the theme for adding a y axis #------------------------------------------------------------------------------- mytheme <- theme_custom() mytheme$axis.line.x <- mytheme$axis.line.y <- mytheme$axis.line mytheme$axis.line.x$colour <- 'white' #------------------------------------------------------------------------------- # Replace the signature number by alphabet letter #------------------------------------------------------------------------------- ConvertNb2Aphabet <- function(c) { if(c == "row1" || c == "col1") { c <- "A" } else if(c == "row2" || c == "col2") { c <- "B"} else if(c == "row3" || c == "col3") { c <- "C"} else if(c == "row4" || c == "col4") { c <- "D"} else if(c == "row5" || c == "col5") { c <- "E"} else if(c == "row6" || c == "col6") { c <- "F"} else if(c == "row7" || c == "col7") { c <- "G"} else if(c == "row8" || c == "col8") { c <- "H"} else if(c == "row9" || c == "col9") { c <- "I"} else if(c == "row10" || c == "col10") { c <- "J"} else if(c == "row11" || c == "col11") { c <- "K"} else if(c == "row12" || c == "col12") { c <- "L"} else if(c == "row13" || c == "col13") { c <- "M"} else if(c == "row14" || c == "col14") { c <- "N"} else if(c == "row15" || c == "col15") { c <- "O"} else if(c == "row16" || c == "col16") { c <- "P"} else if(c == "row17" || c == "col17") { c <- "Q"} else if(c == "row18" || c == "col18") { c <- "R"} else if(c == "row19" || c == "col19") { c <- "S"} else if(c == "row20" || c == "col20") { c <- "T"} else if(c == "row21" || c == "col21") { c <- "U"} else if(c == "row22" || c == "col22") { c <- "V"} else if(c == "row23" || c == "col23") { c <- "W"} else if(c == "row24" || c == "col24") { c <- "X"} else if(c == "row25" || c == "col25") { c <- "Y"} else if(c == "row26" || c == "col26") { c <- "Z"} else { c <- c } } #------------------------------------------------------------------------------- # Check the file doesn't have lines equal to zero #------------------------------------------------------------------------------- CheckFile <- function(rowsum, dataFrame, x) { if(rowsum == 0) { write("\n\nERROR: There is not enough mutations for running NMF!!!", stderr()) write(paste0("Input matrix contains at least one null row ", rownames(dataFrame)[x], "\n\n"), stderr()) stop() } } #------------------------------------------------------------------------------- # Contribution to Signature as the number of SBS per sample #------------------------------------------------------------------------------- Contri2SignSBS <- function(Total_SBS, Percent) { Total_SBS*Percent/100 } #------------------------------------------------------------------------------- # Combined two plots and share the legend #------------------------------------------------------------------------------- grid_arrange_shared_legend <- function(...) { plots <- list(...) g <- ggplotGrob(plots[[1]] + theme(legend.position="bottom"))$grobs legend <- g[[which(sapply(g, function(x) x$name) == "guide-box")]] lheight <- sum(legend$height) grid.arrange( do.call(arrangeGrob, lapply(plots, function(x) x + theme(legend.position="none"))), legend, ncol = 1, heights = unit.c(unit(1, "npc") - lheight, lheight)) } #------------------------------------------------------------------------------- # Calculate the mean of each signatures in each cluster #------------------------------------------------------------------------------- meanCluster <- function(df) { max <- opt$nbSignature+1 sapply(2:max, function(x) { round(mean(as.numeric(as.matrix(df[,x]))), 2) } ) } ############################################################################### # Check file # ############################################################################### # The input musn't contains lines equal to zero !!! matrixNMF <- read.table(opt$input, header=T) # suppresses the return of sapply function invisible( sapply(1:nrow(matrixNMF), function(x) { CheckFile(rowSums(matrixNMF)[x], matrixNMF, x) } ) ) ############################################################################### # Run NMF # ############################################################################### # Create outdir dir.create(opt$output) # Create the output directories output_NMF <- paste0(opt$output, "/NMF") dir.create(output_NMF) output_Figures <- paste0(output_NMF, "/", "Figures") dir.create(output_Figures) output_Files <- paste0(output_NMF, "/", "Files") dir.create(output_Files) # Define the output filenames output_cluster <- paste0(output_Files, "/", "Cluster_MixtureCoeff.txt") figure_cluster <- paste0(output_Figures, "/", "Heatmap_MixtureCoeff.png") output_matrixW <- paste0(output_Files, "/", "MatrixW-Normto100.txt") output_matrixW_ggplot2 <- paste0(output_Files, "/", "MatrixW-Inputggplot2.txt") output_matrixH_ggplot2 <- paste0(output_Files, "/", "MatrixH-Inputggplot2.txt") output_matrixH_cluster <- paste0(output_Files, "/", "Average_ContriByCluster.txt") figure_matrixW_png <- paste0(output_Figures, "/", "CompositionSomaticMutation.png") figure_matrixH_png <- paste0(output_Figures, "/", "ContributionMutationSignature.png") figure_matrixH_cluster <- paste0(output_Figures, "/", "Average_ContriByCluster.png") # Run NMF # request a certain number of cores to use .opt="vP4" nbCPU <- paste0("vP", opt$cpu) res <- nmf(matrixNMF, opt$nbSignature, "brunet", nrun=200, .opt=nbCPU) # If there is more than 300 samples the creation of the heatmap returns an error if(ncol(matrixNMF) <= 300) { # Save the clustered heatmap generated by NMF graphics.off() # close graphics windows options(bitmapType='cairo') png(figure_cluster) coefmap(res, Colv="consensus") dev.off() } # Recover the matrix W and H matrixW <- basis(res) matrixH <- coef(res) # Recover the cluster of the samples matrix_cluster <- cbind(as.numeric(predict(res, what="samples")), colnames(matrixNMF)) colnames(matrix_cluster) <- c("Cluster", "Samples") ## Save the cluster matrix write.table(matrix_cluster, file=output_cluster, quote=F, sep="\t", col.names=T, row.names=F) ############################################################################### # Composition of somatic signatures # ############################################################################### # Normalize to 100% matrixW_norm <- t((t(matrixW)/colSums(matrixW))*100) # Add a column name colnames(matrixW_norm) <- colnames(matrixW_norm, do.NULL = FALSE, prefix = "col") # Replace the name of the columns by the signature name colnames(matrixW_norm) <- sapply(1:length(colnames(matrixW_norm)), function(x) { ConvertNb2Aphabet(colnames(matrixW_norm)[x]) } ) # Split the sequence context from the mutation type context <- c() # Create an empty vector for the sequence context alteration <- c() # Create an empty vector for the mutation type for(i in 1:nrow(matrixW_norm)) { temp <- strsplit((strsplit(rownames(matrixW_norm)[i], ""))[[1]], "") context[i] <- paste0(temp[1], "_", temp[7]) alteration[i] <- paste0(temp[3], temp[4], temp[5]) } # Melt the matrix using the signatures as variable matrixW_melt <- melt(matrixW_norm) # Add columns for the mutation type and the sequence context matrixW_norm <- cbind(matrixW_norm, alteration, context) # Reorder (alteration) for having the same order as in the matrice of published signatures matrixW_norm <- matrixW_norm[order(matrixW_norm[,"alteration"], matrixW_norm[,"context"]), ] # Reorder (columns) for having the same order as in the matrice of published signatures matrixW_norm <- cbind(matrixW_norm[,c("alteration", "context")], matrixW_norm[,1:(ncol(matrixW_norm)-2)]) # Put the column alteration and context at the begining # Save the matrix write.table(matrixW_norm, file=output_matrixW, quote=F, sep="\t", col.names=T, row.names=F) # Add columns for the mutation type and the sequence context matrixW_melt <- cbind(matrixW_melt, alteration) matrixW_melt <- cbind(matrixW_melt, context) # Rename the columns colnames(matrixW_melt) <- c("", "Signature", "value", "alteration", "context") # Save the input for ggplot2 input_ggplot2 <- as.matrix(matrixW_melt) input_ggplot2 <- input_ggplot2[,2:ncol(input_ggplot2)] write.table(input_ggplot2, file=output_matrixW_ggplot2, quote=F, sep="\t", col.names=T, row.names=F) # Maximum value of the y axis max_matrixW <- as.numeric(max(matrixW_melt$value)) # Base plot p <- ggplot(matrixW_melt, aes(x=context, y=value, fill=alteration)) + geom_bar(stat="identity", width=0.5) + facet_grid(Signature ~ alteration, scales="free_y") # Color the mutation types p <- p + scale_fill_manual(values=c("blue", "black", "red", "#828282", "#00CC33", "pink")) # Remove the legend p <- p + guides(fill=FALSE) # Customized theme (no background, no facet grid and strip, y axis only) p <- p + mytheme # Remove the title of the x facet strip p <- p + theme(strip.text.x=element_blank()) # Remove the x axis ticks and title p <- p + theme(axis.title.x=element_blank(), axis.ticks.x = element_blank(), axis.title.y=element_text(size=5)) # Rename the y axis p <- p + ylab("% contribution to signatures") # Set the maximum value of the y axis to the maximum value of the matrix W p <- p + scale_y_continuous(limits=c(0,max_matrixW), oob=squish, breaks=c(0,round(max_matrixW))) # Save some space for adding the sequence context at the bottom p <- p + theme(plot.margin=unit(c(.3, 0, 0, 0), "cm")) p <- p + scale_x_discrete(breaks = c("A_A","A_C","A_G","A_T", "C_A","C_C","C_G","C_T", "G_A","G_C","G_G","G_T", "T_A","T_C","T_G","T_T"), labels =c('A\nA',"\nC","\nG","\nT", 'C\nA',"\nC","\nG","\nT", 'G\nA',"\nC","\nG","\nT", 'T\nA',"\nC","\nG","\nT") ) #------------------------------------------------------------------------------------------------------------------------------ # Change the color of the facets for the mutation type #------------------------------------------------------------------------------------------------------------------------------ cols <- rep( c("blue", "black", "red", "#828282", "#00CC33", "pink")) # Facet strip colours # Make a grob object Pg <- ggplotGrob(p) # To keep track of strip.background grobs idx <- 0 # Find each strip.background and alter its backround colour for( g in 1:length(Pg$grobs) ) { if( grepl( "strip.absoluteGrob" , Pg$grobs[[g]]$name ) ) { idx <- idx + 1 sb <- which( grepl( "strip\\.background" , names( Pg$grobs[[g]]$children ) ) ) Pg$grobs[[g]]$children[[sb]][]$gp$fill <- cols[idx] } } # Reduce the size of the facet strip Pg$heights[[3]] = unit(.05,"cm") #------------------------------------------------------------------------------------------------------------------------------ # Save the graph in a png file #------------------------------------------------------------------------------------------------------------------------------ options(bitmapType='cairo') png(figure_matrixW_png, width=1300, heigh=500, res=300, pointsize = 4) plot(Pg) ## Add label for the mutation type above the strip facet grid.text(0.12, unit(1,"npc") - unit(1.4,"line"), label="C>A") grid.text(0.27, unit(1,"npc") - unit(1.4,"line"), label="C>G") grid.text(0.42, unit(1,"npc") - unit(1.4,"line"), label="C>T") grid.text(0.58, unit(1,"npc") - unit(1.4,"line"), label="T>A") grid.text(0.74, unit(1,"npc") - unit(1.4,"line"), label="T>C") grid.text(0.89, unit(1,"npc") - unit(1.4,"line"), label="T>G") invisible( dev.off() ) ############################################################################### # Contribution of mutational signature in each samples # ############################################################################### # Calculate the variability expain by the model (evar) rss <- rss(res, matrixNMF) varTot <- sum(matrixNMF^2) evar <- 1 - rss / varTot evar_round <- round(evar, digits=3) * 100 if(is.null(opt$html)) { cat("\n", evar_round, "% of the variance is explained with", opt$nbSignature, "signatures\n\n") } # Recover the total number of SBS per samples NbSBS <- colSums(matrixNMF) # Normalized matrix H to 100% matrixH_norm <- t((t(matrixH)/colSums(matrixH))*100) # Add a row name rownames(matrixH_norm) <- rownames(matrixH_norm, do.NULL = FALSE, prefix = "row") # Replace the signature number by letter rownames(matrixH_norm) <- sapply(1:length(rownames(matrixH_norm)), function(x) { ConvertNb2Aphabet(rownames(matrixH_norm)[x]) } ) ## Combined the contribution with the total number of SBS matrixH_norm_melt <- melt(matrixH_norm) matrixH_norm_melt <- cbind(matrixH_norm_melt, rep(NbSBS, each = opt$nbSignature)) colnames(matrixH_norm_melt) <- c("Signature", "Sample", "Percent_Contri", "Total_SBS") # Calculate the contribution in number of SBS matrixH_norm_melt$ContriSBS <- sapply(1:nrow(matrixH_norm_melt), function(x) { Contri2SignSBS(matrixH_norm_melt$Total_SBS[x], matrixH_norm_melt$Percent_Contri[x]) } ) colnames(matrixH_norm_melt) <- c("Signature", "Sample", "Percent_Contri", "Total_SBS", "CountSBS_Contri") # Save the matrix write.table(matrixH_norm_melt, file=output_matrixH_ggplot2, quote=F, sep="\t", col.names=T, row.names=F) # Base plot for the contribution of each samples according the count of mutations p2 <- ggplot(matrixH_norm_melt, aes(x=reorder(Sample, -CountSBS_Contri), y=CountSBS_Contri, fill=Signature)) + geom_bar(stat="identity") + theme_classic() # Reverse the y axis p2 <- p2 + scale_y_reverse() # Rename the y and x axis p2 <- p2 + ylab("Number of mutations") + xlab("Samples") # Remove the x axis line p2 <- p2 + theme(axis.line.x=element_blank()) # Add sample names if(ncol(matrixNMF) <= 35) { p2 <- p2 + theme(axis.text.x = element_text(angle=90)) } else { p2 <- p2 + theme(axis.text.x = element_blank()) } # Base plot for the contribution of each samples in percentages p3 <- ggplot(matrixH_norm_melt, aes(x=reorder(Sample, -CountSBS_Contri), y=Percent_Contri, fill=Signature)) + geom_bar(stat="identity") + theme_classic() + theme(axis.text.x = element_blank()) + xlab("") + ylab("% of mutations") # Remove the x axis line p3 <- p3 + theme(axis.line.x=element_blank(), axis.ticks.x=element_blank()) # Plot PNG png(figure_matrixH_png, width=3000, heigh=2000, res=300) # Combined the two plots for the contribution of the samples suppressWarnings( grid_arrange_shared_legend(p3, p2) ) invisible( dev.off() ) ############################################################################### # Average contributions of each signature in each cluster # ############################################################################### matrixH_cluster <- cbind(matrix_cluster[,1], t(matrixH_norm)) colnames(matrixH_cluster) <- c("Cluster", colnames(t(matrixH_norm))) df <- as.data.frame(matrixH_cluster) tmp_mat <- sapply(1:opt$nbSignature, function(x) { meanCluster(df[df[,1] == x,]) } ) # Add a name for the row and the col rownames(tmp_mat) <- sapply(1:opt$nbSignature, function(x) { paste0("Sig. ", x) } ) colnames(tmp_mat) <- sapply(1:opt$nbSignature, function(x) { paste0("Cluster ", x) } ) tmp_mat <- t(tmp_mat) # Recover the number of samples in each cluster nbSampleByCluster <- sapply(1:opt$nbSignature, function(x) { as.numeric( strsplit( as.character(dim(df[df[,1] == x,])), " " ) ) } ) # Combined the average contribution and the number of samples tmp_mat <- cbind(tmp_mat, nbSampleByCluster[1,]) # Add a name for the row and the col colnames(tmp_mat)[opt$nbSignature+1] <- "Number of samples" # Save the matrix write.table(tmp_mat, file=output_matrixH_cluster, quote=F, sep="\t", col.names=T, row.names=T) ## Create an image of the table with ggplot2 # Dummy plot p4 <- qplot(1:10, 1:10, geom = "blank") + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.border = element_rect(fill=NA,color="white", size=0.5, linetype="solid"), axis.line = element_blank(), axis.ticks = element_blank(), panel.background = element_rect(fill="white"), plot.background = element_rect(fill="white"), legend.position = "none", axis.text = element_blank(), axis.title = element_blank() ) # Adding a table p4 <- p4 + annotation_custom(grob = tableGrob(tmp_mat), xmin = 4, xmax = 7, ymin = 0, ymax = 10) # Save the table png(figure_matrixH_cluster, width=2500, heigh=1000, res=300) # Combined the two plots for the contribution of the samples plot(p4) invisible( dev.off() ) # Delete the empty plot created by the script if (file.exists("Rplots.pdf")) invisible( file.remove("Rplots.pdf") ) ############################################################################### # Create HTML output for Galaxy # ############################################################################### if(! is.null(opt$html)) { # Galaxy doesn't need the full path to the files so redefine the output filenames output_cluster_html <- paste0("NMF/Files/Cluster_MixtureCoeff.txt") figure_cluster_html <- paste0("NMF/Figures/Heatmap_MixtureCoeff.png") output_matrixW_html <- paste0("NMF/Files/MatrixW-Normto100.txt") output_matrixH_ggplot2_html <- paste0("NMF/Files/MatrixH-Inputggplot2.txt") output_matrixH_cluster_html <- paste0("NMF/Files/Average_ContriByCluster.txt") figure_matrixW_png_html <- paste0("NMF/Figures/CompositionSomaticMutation.png") figure_matrixH_png_html <- paste0("NMF/Figures/ContributionMutationSignature.png") figure_matrixH_cluster_html <- paste0("NMF/Figures/Average_ContriByCluster.png") #### Create an archive with all the results setwd(opt$output) # zip("NMF.tar.gz", "NMF") system("zip -r NMF.zip NMF") write("<html><body>", file=opt$html) write("<center> <h2> NMF Mutational signatures analysis </h2> </center>", file=opt$html, append=TRUE) write("<br/> Download the results", file=opt$html, append=TRUE) write("<br/><a href=NMF.zip>NMF.zip</a><br/>", file=opt$html, append=TRUE) #### Heatmap write("<table>", file=opt$html, append=TRUE) write("<tr> <br/> <th><h3>Heatmap of the mixture coefficient matrix</h3></th> </tr>", file=opt$html, append=TRUE) write(paste0("<tr> <td> <center> <br/> <a href=", output_cluster_html, ">Cluster_MixtureCoeff.txt</a> </center> </td> </tr>"), file=opt$html, append=TRUE) write("<tr>", file=opt$html, append=TRUE) if(!file.exists(figure_cluster)) { write("WARNING: NMF package can't plot the heatmap when the samples size is above 300. <br/>", file=opt$html, append=TRUE) }else{ write(paste0("<td> <center> <a href=", figure_cluster_html, ">"), file=opt$html, append=TRUE) write(paste0("<img src=", figure_cluster_html, "/></a> <center> </td>"), file=opt$html, append=TRUE) } write("</tr>", file=opt$html, append=TRUE) write("</table>", file=opt$html, append=TRUE) ### Signature composition write("<br/><br/>", file=opt$html, append=TRUE) write("<table>", file=opt$html, append=TRUE) write("<tr>", file=opt$html, append=TRUE) write("<th><h3>Signature composition</h3></th>", file=opt$html, append=TRUE) write("</tr>", file=opt$html, append=TRUE) write(paste0("<tr><td>", evar_round, "% of the variance is explained with ", opt$nbSignature, " signatures", "</td></tr>"), file=opt$html, append=TRUE) write("<tr height=15></tr>", file=opt$html, append=TRUE) write(paste0("<tr><td> <center> <a href=", output_matrixW_html ,">Composition somatic mutation (input matrix for the tool MutSpec-Compare)</a><center></td></tr>"), file=opt$html, append=TRUE) write("<tr>", file=opt$html, append=TRUE) write(paste0("<td><a href=", figure_matrixW_png_html, ">"), file=opt$html, append=TRUE) write(paste0("<img width=1000 src=", figure_matrixW_png_html, "/></a></td>"), file=opt$html, append=TRUE) write("</tr> ", file=opt$html, append=TRUE) write("</table>", file=opt$html, append=TRUE) write("<br/><br/>", file=opt$html, append=TRUE) ### Sample contribution to signatures write("<table>", file=opt$html, append=TRUE) write("<tr>", file=opt$html, append=TRUE) write("<th><h3>Sample contribution to signatures</h3></th>", file=opt$html, append=TRUE) write("</tr>", file=opt$html, append=TRUE) write(paste0("<tr><td> <center> <a href=", output_matrixH_ggplot2_html, ">Contribution mutation signature matrix</a></center></td></tr>"), file=opt$html, append=TRUE) write("<tr>", file=opt$html, append=TRUE) write(paste0("<td><a href=", figure_matrixH_png_html, ">"), file=opt$html, append=TRUE) write(paste0("<img width=700 src=", figure_matrixH_png_html, "/></a></td>"), file=opt$html, append=TRUE) write("</tr>", file=opt$html, append=TRUE) write("</table>", file=opt$html, append=TRUE) write("<br/><br/>", file=opt$html, append=TRUE) ### Average contributions of each signatures in each cluster write("<table>", file=opt$html, append=TRUE) write("<tr>", file=opt$html, append=TRUE) write("<th><h3>Average contributions of each signatures in each cluster</h3></th>", file=opt$html, append=TRUE) write(paste0("<tr><td> <center> <a href=", output_matrixH_cluster_html, ">Average contributions</a></center></td></tr>"), file=opt$html, append=TRUE) write("<tr>", file=opt$html, append=TRUE) write(paste0("<td><a href=", figure_matrixH_cluster_html, ">"), file=opt$html, append=TRUE) write(paste0("<img width=700 src=", figure_matrixH_cluster_html, "/></a></td>"), file=opt$html, append=TRUE) write("</tr> ", file=opt$html, append=TRUE) write("</table>", file=opt$html, append=TRUE) write("<br/><br/>", file=opt$html, append=TRUE) write("<br/><br/><br/><br/>", file=opt$html, append=TRUE) }