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ARTbio/tools-artbio,drosofff/tools-artbio,ARTbio/tools-artbio,drosofff/tools-artbio,drosofff/tools-artbio,drosofff/tools-artbio,ARTbio/tools-artbio
## 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("-f", "--first_dataframe"), type="character", help="path to first dataframe"),
    make_option(c("-e", "--extra_dataframe"), type="character", help="path to additional dataframe"),
    make_option("--first_plot_method", type = "character", help="How additional data should be plotted"),
    make_option("--extra_plot_method", type = "character", help="How additional data should be plotted"),
    make_option("--output_pdf", type = "character", help="path to the pdf file with plots")
    )
 
parser <- OptionParser(usage = "%prog [options] file", option_list = option_list)
args = parse_args(parser)
 
# data frames implementation
## first table
Table = read.delim(args$first_dataframe, header=T, row.names=NULL)
if (args$first_plot_method == "Counts") {
    Table <- within(Table, Counts[Polarity=="R"] <- (Counts[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)$Chrom_length)) )
n_genes=length(per_gene_readmap)
# second table
if (args$extra_plot_method != '') {
    ExtraTable=read.delim(args$extra_dataframe, header=T, row.names=NULL)
    if (args$extra_plot_method=='Size') {
        ExtraTable <- within(ExtraTable, Count[Polarity=="R"] <- (Count[Polarity=="R"]*-1))
        }
    per_gene_size=lapply(genes, function(x) subset(ExtraTable, Chromosome==x))
    }
    
## end of data frames implementation

## functions

plot_unit = function(df, method=args$first_plot_method, ...) {
    if (method == 'Counts') {
        p = xyplot(Counts~Coordinate|factor(Dataset, levels=unique(Dataset))+factor(Chromosome, levels=unique(Chromosome)),
        data=df,
        type='h',
        lwd=1.5,
        scales= list(relation="free", x=list(rot=0, cex=0.7, axs="i", tck=0.5), y=list(tick.number=4, rot=90, cex=0.7)),
        xlab=NULL, main=NULL, ylab=NULL,
        as.table=T,
        origin = 0,
        horizontal=FALSE,
        group=Polarity,
        col=c("red","blue"),
        par.strip.text = list(cex=0.7),
        ...)
    } else if (method != "Size") {
        p = xyplot(eval(as.name(method))~Coordinate|factor(Dataset, levels=unique(Dataset))+factor(Chromosome, levels=unique(Chromosome)),
        data=df,
        type='p',
        cex=0.35,
        pch=19,
        scales= list(relation="free", x=list(rot=0, cex=0, axs="i", tck=0.5), y=list(tick.number=4, rot=90, cex=0.7)),
        xlab=NULL, main=NULL, ylab=NULL,
        as.table=T,
        origin = 0,
        horizontal=FALSE,
        group=Polarity,
        col=c("darkred","darkblue"),
        par.strip.text = list(cex=0.7),
        ...)
    }
    else {
        p = barchart(Count~as.factor(Size)|factor(Dataset, levels=unique(Dataset))+Chromosome, data = df, origin = 0,
        horizontal=FALSE,
        group=Polarity,
        stack=TRUE,
        col=c('red', 'blue'),
        cex=0.75,
        scales=list(y=list(tick.number=4, rot=90, relation="free", cex=0.7), x=list(cex=0.7) ),
        xlab = NULL,
        ylab = NULL,
        main = NULL,
        as.table=TRUE,
        newpage = T,
        par.strip.text = list(cex=0.7),
        ...)
    }
    if (args$extra_plot_method != '') {
    combineLimits(p)
    }
}

## end of functions

## function parameters
par.settings.firstplot = list(layout.heights=list(top.padding=-1, bottom.padding = -3), plot.margin=unit(c(-0.5,1,1,1), "cm"))
par.settings.secondplot=list(layout.heights=list(top.padding=-1, bottom.padding = -3), strip.background=list(col=c("deepskyblue","lavender")) )
title_first_method = list(Counts="Read Counts", Coverage="Coverage depths", Median="Median sizes", Mean="Mean sizes", Size="Size Distributions")
title_extra_method = list(Counts="Read Counts", Coverage="Coverage depths", Median="Median sizes", Mean="Mean sizes", Size="Size Distributions")
legend_first_method =list(Counts="Read count", Coverage="Coverage depth", Median="Median size", Mean="Mean size", Size="Read count")
legend_extra_method =list(Counts="Read count", Coverage="Coveragedepth", Median="Median size", Mean="Mean size", Size="Read count")
bottom_first_method =list(Counts="Coordinates (nbre of bases)",Coverage="Coordinates (nbre of bases)", Median="Coordinates (nbre of bases)", Mean="Coordinates (nbre of bases)", Size="Sizes of reads")
bottom_extra_method =list(Counts="Coordinates (nbre of bases)",Coverage="Coordinates (nbre of bases)", Median="Coordinates (nbre of bases)", Mean="Coordinates (nbre of bases)", Size="Sizes of reads")
## end of function parameters'

## GRAPHS

if (n_genes > 5) {page_height_simple = 16; page_height_combi=16; rows_per_page=10} else { # 11.69
                 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$output_pdf, paper="special", height=page_height_simple, width=page_width)
if (rows_per_page %% 2 != 0) { rows_per_page = rows_per_page + 1}
for (i in seq(1,n_genes,rows_per_page/2)) {
    start=i
    end=i+rows_per_page/2-1
    if (end>n_genes) {end=n_genes}
    first_plot.list = lapply(per_gene_readmap[start:end], function(x) plot_unit(x, strip=FALSE, par.settings=par.settings.firstplot))
    second_plot.list = lapply(per_gene_size[start:end], function(x) plot_unit(x, method=args$extra_plot_method, par.settings=par.settings.secondplot))
    plot.list=rbind(second_plot.list, first_plot.list)
    args_list=c(plot.list, list(nrow=rows_per_page+1, ncol=1, heights=rep(10,11),
                                top=textGrob(paste(title_first_method[[args$first_plot_method]], "and", title_extra_method[[args$extra_plot_method]]), gp=gpar(cex=1), vjust=2, just="top"),
                                left=textGrob(paste(legend_first_method[[args$first_plot_method]], "/", legend_extra_method[[args$extra_plot_method]]), gp=gpar(cex=1), vjust=2, rot=90),
                                sub=textGrob(paste(bottom_first_method[[args$first_plot_method]], "/", bottom_extra_method[[args$extra_plot_method]]), gp=gpar(cex=1), just="bottom")
                                )
               )
do.call(grid.arrange, args_list)
}
devname=dev.off()


## 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("-f", "--first_dataframe"), type="character", help="path to first dataframe"),
    make_option(c("-e", "--extra_dataframe"), type="character", help="path to additional dataframe"),
    make_option("--extra_plot_method", type = "character", help="How additional data should be plotted"),
    make_option("--output_pdf", type = "character", help="path to the pdf file with plots")
    )
 
parser <- OptionParser(usage = "%prog [options] file", option_list = option_list)
args = parse_args(parser)
 
# data frames implementation

Table = read.delim(args$first_dataframe, header=T, row.names=NULL)
Table <- within(Table, Counts[Polarity=="R"] <- (Counts[Polarity=="R"]*-1))
n_samples=length(unique(Table$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)

ExtraTable=read.delim(args$extra_dataframe, header=T, row.names=NULL)
if (args$extra_plot_method=='Size') {
    ExtraTable <- within(ExtraTable, Count[Polarity=="R"] <- (Count[Polarity=="R"]*-1))
    }
per_gene_size=lapply(genes, function(x) subset(ExtraTable, Chromosome==x))
    
## end of data frames implementation

## functions

first_plot = function(df, ...) {
    p = xyplot(Counts~Coordinate|factor(Dataset, levels=unique(Dataset))+factor(Chromosome, levels=unique(Chromosome)),
    data=df,
    type='h',
    lwd=1.5,
    scales= list(relation="free", x=list(rot=0, cex=0.7, 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("red","blue"),
    par.strip.text = list(cex=0.7),
    ...)
    combineLimits(p)
}


second_plot = function(df, method=args$extra_plot_method, ...) {
  if (method != "Size") {
    p = xyplot(eval(as.name(args$extra_plot_method))~Coordinate|factor(Dataset, levels=unique(Dataset))+factor(Chromosome, levels=unique(Chromosome)),
    data=df,
    type='p',
    cex=0.35,
    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),
    ...)
    }
    else {
    p = barchart(Count~as.factor(Size)|factor(Dataset, levels=unique(Dataset))+Chromosome, data = df, origin = 0,
    horizontal=FALSE,
    group=Polarity,
    stack=TRUE,
    col=c('red', 'blue'),
    cex=0.75,
    scales=list(y=list(tick.number=4, rot=90, relation="free", cex=0.7), x=list(cex=0.7) ),
    xlab = NULL,
    ylab = NULL,
    main = NULL,
    as.table=TRUE,
    newpage = T,
    par.strip.text = list(cex=0.7),
    ...)
    }    
    combineLimits(p)
}

## end of functions

## function parameters
par.settings.firstplot = list(layout.heights=list(top.padding=0, bottom.padding=0), strip.background = list(col=c("lightblue","lightgreen")) )
par.settings.secondplot=list(layout.heights=list(top.padding=0, bottom.padding=0))
graph_title=list(Coverage="Read Maps and Coverages", Median="Read Maps and Median sizes", Mean="Read Maps and Mean sizes", SizeDistribution="Read Maps and Size Distributions")
graph_legend=list(Coverage="Read counts / Coverage", Median="Read counts / Median size", Mean="Read counts / Mean size", SizeDistribution="Read counts")
graph_bottom=list(Coverage="Nucleotide coordinates", Median="Nucleotide coordinates", Mean="Nucleotide coordinates", Size="Read sizes / Nucleotide coordinates")
## end of function parameters'

## GRAPHS

if (n_genes > 5) {page_height_simple = 11.69; page_height_combi=11.69; rows_per_page=6} 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$output_pdf, paper="special", height=page_height_simple, width=page_width)
if (rows_per_page %% 2 != 0) { rows_per_page = rows_per_page + 1}
for (i in seq(1,n_genes,rows_per_page/2)) {
    start=i
    end=i+rows_per_page/2-1
    if (end>n_genes) {end=n_genes}
    first_plot.list = lapply(per_gene_readmap[start:end], function(x) first_plot(x, strip=FALSE, par.settings=par.settings.firstplot))
    second_plot.list = lapply(per_gene_size[start:end], function(x) second_plot(x, method=args$extra_plot_method, par.settings=par.settings.secondplot))
    plot.list=rbind(second_plot.list, first_plot.list)
    args_list=c(plot.list, list(nrow=rows_per_page+1, ncol=1,
                                    top=textGrob(graph_title[[args$extra_plot_method]], gp=gpar(cex=1), just="top"),
                                    left=textGrob(graph_legend[[args$extra_plot_method]], gp=gpar(cex=1), vjust=1, rot=90),
                                    sub=textGrob(graph_bottom[[args$extra_plot_method]], gp=gpar(cex=1), just="bottom")
                                    )
           )
do.call(grid.arrange, args_list)
}
devname=dev.off()

