Mercurial > repos > artbio > small_rna_map
view lattice_small_rna_map.r @ 3:2e0dc6032a98 draft
planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit 93f212712d9846c7aaa389de60babb332d38363e
author | artbio |
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date | Tue, 18 Jul 2017 13:34:36 -0400 |
parents | |
children | 6ff925458e05 |
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## Setup R error handling to go to stderr #options( show.error.messages=F, # error = function () { cat( geterrmessage(), file=stderr() ); q( "no", 1, F ) } ) warnings() library(RColorBrewer) library(lattice) library(latticeExtra) library(grid) library(gridExtra) library(optparse) option_list <- list( make_option(c("-r", "--output_tab"), type="character", help="path to tabular file"), make_option("--output_pdf", type = "character", help="path to the pdf file with plot") ) parser <- OptionParser(usage = "%prog [options] file", option_list = option_list) args = parse_args(parser) # dataset manipulation Table = read.delim(args$output_tab, header=T, row.names=NULL) Table <- within(Table, Nbr_reads[Polarity=="R"] <- (Nbr_reads[Polarity=="R"]*-1)) n_samples=length(unique(Table$Dataset)) genes=unique(levels(Table$Chromosome)) per_gene_readmap=lapply(genes, function(x) subset(Table, Chromosome==x)) per_gene_limit=lapply(genes, function(x) c(1, unique(subset(Table, Chromosome==x)$Chrom_length)) ) n_genes=length(per_gene_readmap) ## end of data frames implementation ## functions plot_readmap=function(df, ...) { combineLimits(xyplot(Nbr_reads~Coordinate|factor(Dataset, levels=unique(Dataset))+factor(Chromosome, levels=unique(Chromosome)), data=df, type='h', scales= list(relation="free", x=list(rot=0, cex=0.7, axs="i", tck=0.1), y=list(tick.number=4, rot=90, cex=0.7)), xlab=NULL, main=NULL, ylab=NULL, as.table=T, origin = 0, horizontal=FALSE, group=Polarity, col=c("red","blue"), par.strip.text = list(cex=0.7), ...)) } plot_size=function(df, ...) { smR.prepanel=function(x,y,...) {; yscale=c(y*0, max(abs(y)));list(ylim=yscale);} sizeplot = xyplot(Median~Coordinate|factor(Dataset, levels=unique(Dataset))+factor(Chromosome, levels=unique(Chromosome)), data=df, type='p', cex=0.5, pch=19, scales= list(relation="free", x=list(rot=0, cex=0, axs="i", tck=0.5), y=list(tick.number=4, rot=90, cex=0.7)), xlab=NULL, main=NULL, ylab=NULL, as.table=T, origin = 0, horizontal=FALSE, group=Polarity, col=c("darkred","darkblue"), par.strip.text = list(cex=0.7), ...) combineLimits(sizeplot) } ## end of functions ## function parameters par.settings.readmap=list(layout.heights=list(top.padding=0, bottom.padding=0), strip.background = list(col=c("lightblue","lightgreen")) ) par.settings.size=list(layout.heights=list(top.padding=0, bottom.padding=0)) ## end of function parameters' ## GRAPHS if (n_genes > 7) {page_height_simple = 11.69; page_height_combi=11.69; rows_per_page=10} else { rows_per_page= n_genes; page_height_simple = 2.5*n_genes; page_height_combi=page_height_simple*2 } if (n_samples > 4) {page_width = 8.2677*n_samples/4} else {page_width = 8.2677*n_samples/2} # to test pdf(file=args$output_pdf, paper="special", height=page_height_simple, width=page_width) if (rows_per_page %% 2 != 0) { rows_per_page = rows_per_page + 1} for (i in seq(1,n_genes,rows_per_page/2)) { start=i end=i+rows_per_page/2-1 if (end>n_genes) {end=n_genes} readmap_plot.list=lapply(per_gene_readmap[start:end], function(x) plot_readmap(x, xlim=c(1, x$Chrom_length[1]), strip=FALSE, par.settings=par.settings.readmap)) size_plot.list=lapply(per_gene_readmap[start:end], function(x) plot_size(x, xlim=c(1, x$Chrom_length[1]), par.settings=par.settings.size)) plot.list=rbind(size_plot.list, readmap_plot.list) args_list=c(plot.list, list(nrow=rows_per_page+1, ncol=1, top=textGrob("Read Maps and Median sizes", gp=gpar(cex=1), just="top"), left=textGrob("Read counts / Median size", gp=gpar(cex=1), vjust=1, rot=90), sub=textGrob("Nucleotide coordinates", gp=gpar(cex=1), just="bottom") ) ) do.call(grid.arrange, args_list) } devname=dev.off()