<tool id="Readmap" name="Generate readmap and histograms from alignment files" version="0.9.2">
  <description>from sRbowtie aligment</description>
  <requirements><requirement type='package'>bowtie-inspect</requirement></requirements>
  <parallelism method="basic"></parallelism>
<command interpreter="python">
        readmap.py 
	          #if $refGenomeSource.genomeSource == "history":
         	    --reference_fasta  ## sys.argv[2]
                    $refGenomeSource.ownFile ## index source
          	  #else:
                    #silent reference= filter( lambda x: str( x[0] ) == str( $refGenomeSource.series[0].input.dbkey ), $__app__.tool_data_tables[ 'bowtie_indexes' ].get_fields() )[0][-1]
		    --reference_bowtie_index
                    $reference
          	  #end if
		  --rcode
		  $plotCode
		  --output_readmap
		  $readmap_dataframe
		  --output_size_distribution
		  $size_distribution_dataframe
		  --minquery
		  $minquery
		  --maxquery
		  $maxquery
		  --input
		  #for $i in $refGenomeSource.series
    		    $i.input 
		  #end for
		  --ext
		  #for $i in $refGenomeSource.series
    		    $i.input.ext 
		  #end for
		  --label
		  #for $i in $refGenomeSource.series
    		    "$i.input.name" 
		  #end for
		  --normalization_factor
		  #for $i in $refGenomeSource.series
    		    $i.norm
		  #end for
		  #if $gff:
		    --gff
                    $gff
                  #end if

</command>
  <inputs>
       <conditional name="refGenomeSource">
           <param name="genomeSource" type="select" label="Will you select a reference genome from your history or use a built-in index?" help="Built-ins were indexed using default options">
               <option value="indexed">Use a built-in index</option>
               <option value="history">Use one from the history</option>
           </param>
           <when value="indexed">
	     <repeat name="series" title="Add alignment files">
	       <param name="input" type="data" label="Select multiple alignments to parse">
                  <validator type="dataset_metadata_in_data_table" table_name="bowtie_indexes" metadata_name="dbkey" metadata_column="0" message="database not set for this bowtie output. Select the database(=genome used for matching) manually, or select a reference fasta from your history."/>
               </param>
	       <param name="norm" type="float" value="1" label="Indicate a normalization factor to compare multiple aligments"/>
	     </repeat>
           </when>
           <when value="history">
	     <repeat name="series" title="Add alignment files">
	       <param name="input" type="data" label="Select multiple alignments to parse"/>
	       <param name="norm" type="integer" value="1" label="Indicate a normalization factor to compare multiple aligments"/>
	     </repeat>
	   </when>
       </conditional>
                <param name="gff" type="data" optional="true" label="Optional: select a GFF to investigate regions of interest" help="GFF must match genome build"/>
                 <!-- <validator type="dataset_metadata_in_data_table" table_name="bowtie_indexes" metadata_name="dbkey" metadata_column="0" message="GFF database and alignment file databse do not match!"/> -->
                <param name="minquery" type="integer" size="3" value="18" label="Min size of query small RNAs" help="'18' = 18 nucleotides"/>
                <param name="maxquery" type="integer" size="3" value="28" label="Max size of query small RNAs" help="'28' = 28 nucleotides"/>
                <param name="title" type="text" size="15" value= "Readmaps and size distributions" label="Main Titles"/>
                <param name="xlabel" type="text" size="15" value="Coordinates/read size" label="x axis label"/>
                <param name="ylabel" type="text" size="15" value="Number of reads" label="y axis label"/>
                <param name="rows_per_page" type="text" size="9" value="8" label="How many items to display per page?">
		  <validator type="in_range" min="6" max="20" message="Select between 6 and 20 rows, as the readability will suffer otherwise."/>
                </param>
  </inputs>
   <configfiles>
     <configfile name="plotCode">
      ## Setup R error handling to go to stderr
      options( show.error.messages=F,
               error = function () { cat( geterrmessage(), file=stderr() ); q( "no", 1, F ) } )
      library(RColorBrewer)
      library(lattice)
      library(latticeExtra)
      library(grid)
      library(gridExtra)
      ##cheetahtemplate data frame implementation

      rm=read.delim("${readmap_dataframe}", header=T, row.names=NULL)
      pdf(file="${readmap_PDF}", paper="special", height=11.69, width=8.2677)
      n_samples=length(unique(rm\$sample))

      genes=unique(levels(rm\$gene))
      per_gene_readmap=lapply(genes, function(x) subset(rm, gene==x))
      n_genes=length(per_gene_readmap)
      

      par.settings.readmap=list(layout.heights=list(top.padding=0, bottom.padding=-3), fontsize = list(text=96/${rows_per_page}, points=8))
      par.settings.size=list(layout.heights=list(top.padding=-1, bottom.padding=-3), fontsize = list(text=96/${rows_per_page}, points=8))
      par.settings.combination.readmap=list(layout.heights=list(top.padding=0, bottom.padding=-3), fontsize = list(text=96/${rows_per_page}, points=8))
      par.settings.combination.size=list(layout.heights=list(top.padding=-2, bottom.padding=-0.5), fontsize = list(text=96/${rows_per_page}, points=8))
      

      plot_readmap=function(df, ...) {
      combineLimits(xyplot(count~coord|factor(sample, levels=unique(sample))+reorder(gene, count, function(x) -sum(abs(x))), 
      data=df, 
      type='h', 
      scales= list(relation="free", x=list(rot=0, cex=0.75, axs="i", tck=0.5), y=list(tick.number=4, rot=90, cex=0.75)),
      xlab=NULL, main=NULL, ylab=NULL, 
      as.table=T, 
      origin = 0, 
      horizontal=FALSE, 
      group=polarity,
      col=c("red","blue"),
      ...))
      }

      plot_size_distribution= function(df, ...) {
          smR.prepanel=function(x,y,...){; yscale=c(-max(abs(y)), max(abs(y)));list(ylim=yscale);}
         bc= barchart(count~as.factor(size)|factor(sample, levels=unique(sample))+gene, 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=0.75),
          prepanel=smR.prepanel,
          xlab = NULL,
          ylab = NULL,
#          par.settings=list(layout.heights=list(top.padding=-2, bottom.padding=-3), fontsize = list(text=8, points=8)),
          main = NULL , as.table=TRUE, newpage = T, ...)
          combineLimits(bc)
          }

      for (i in seq(1,n_genes,${rows_per_page})) {
        start=i
        end=i+${rows_per_page}-1
        if (end>n_genes) {end=n_genes}
	readmap_plot.list=lapply(per_gene_readmap[start:end], function(x) plot_readmap(x, par.settings=par.settings.readmap))
	args.list=c(readmap_plot.list, list(nrow=${rows_per_page}, ncol=1, main="readmaps", left="${ylabel}", sub="readmap coordinate"))
        do.call(grid.arrange, args.list)
      }

      devname=dev.off()

      size=read.delim("${size_distribution_dataframe}", header=T, row.names=NULL)
      per_gene_size=lapply(genes, function(x) subset(size, gene==x))

      pdf(file="${size_PDF}", paper="special", height=11.69, width=8.2677)

      for (i in seq(1,n_genes,${rows_per_page})) {
        start=i
        end=i+${rows_per_page}-1
        if (end>n_genes) {end=n_genes}
        plot.list=lapply(per_gene_size[start:end], function(x) plot_size_distribution(x, par.settings=par.settings.size))
        args.list=c(plot.list, list(nrow=${rows_per_page}, ncol=1, main="size distribution", left="${ylabel}", sub="readsize in nucleotides"))
        do.call(grid.arrange, args.list)
      }

      devname=dev.off()

      pdf(file="${combi_PDF}", paper="special", height=11.69, width=8.2677)

      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}
	read_plot.list=lapply(per_gene_readmap[start:end], function(x) plot_readmap(x, par.settings=par.settings.combination.readmap))
        size_plot.list=lapply(per_gene_size[start:end], function(x) plot_size_distribution(x, strip=FALSE, par.settings=par.settings.combination.size))
	plot.list=rbind(read_plot.list, size_plot.list )
        args.list=c(plot.list, list(nrow=${rows_per_page}, ncol=1, main="${title}", left="${ylabel}", sub="${xlabel}"))
        do.call(grid.arrange, args.list)
      }

      devname=dev.off()


     </configfile>
   </configfiles>

   <outputs>
   <data format="tabular" name="readmap_dataframe" label="Readmap dataframe"/>
   <data format="tabular" name="size_distribution_dataframe" label="Size distribution dataframe"/>
   <data format="pdf" name="readmap_PDF" label="Readmaps"/>
   <data format="pdf" name="size_PDF" label="Size distribution"/>
   <data format="pdf" name="combi_PDF" label="Size distribution and Readmaps"/>
   </outputs>
<help>

**What it does**

Takes one or more alignment files (BAM, SAM or tabular bowtie output) as input and produces a "Readmap", 
where by default for each "chromosome" the position of the read is recorded on the x-axis, and the y-axis indicates 
the number of reads per position. Reads that map in sense are on the top, reads that map antisense are on the bottom.


.. class:: warningmark

'''TIP''' The input data can be produced using the sRbowtie tool.

----

'''Example'''

Query sequence::
For a SAM file as the following:

  5	16	2L_79	24393	255	17M	*	0	0	CCTTCATCTTTTTTTTT	IIIIIIIIIIIIIIIII	XA:i:0	MD:Z:17	NM:i:0

  11	0	2R_1	12675	255	21M	*	0	0	AAAAAAAACGCGTCCTTGTGC	IIIIIIIIIIIIIIIIIIIII	XA:i:0	MD:Z:21	NM:i:0

  2	16	2L_5	669	255	23M	*	0	0	TGTTGCTGCATTTCTTTTTTTTT	IIIIIIIIIIIIIIIIIIIIIII	XA:i:0	MD:Z:23	NM:i:0

produce a plot like this:

----

.. image:: static/images/readmap.png 
    :height: 800 
    :width: 500

</help>
</tool>