# HG changeset patch
# User artbio
# Date 1500399276 14400
# Node ID 2e0dc6032a98f31921794dc41ab86a0cf57bc78a
# Parent  7feee0446c5c2fdc153638c4279affecdb6221b4
planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit 93f212712d9846c7aaa389de60babb332d38363e

diff -r 7feee0446c5c -r 2e0dc6032a98 lattice_small_rna_map.r
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/lattice_small_rna_map.r	Tue Jul 18 13:34:36 2017 -0400
@@ -0,0 +1,102 @@
+## 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()
+
diff -r 7feee0446c5c -r 2e0dc6032a98 small_rna_map.py
--- a/small_rna_map.py	Wed Jul 12 13:40:36 2017 -0400
+++ b/small_rna_map.py	Tue Jul 18 13:34:36 2017 -0400
@@ -1,84 +1,80 @@
-import os
-from os.path import basename
+import argparse
+from collections import defaultdict
+
+import numpy
+
 import pysam
-import argparse
-import numpy
-import collections
 
 
 def Parser():
     the_parser = argparse.ArgumentParser()
-    the_parser.add_argument('--input', dest="input", required=True, nargs='+', help='input BAM files')
-    the_parser.add_argument('--output', action="store", type=str, help="output tabular file")
+    the_parser.add_argument('--input', dest='input', required=True,
+                            nargs='+', help='input BAM files')
+    the_parser.add_argument('--sample_name', dest='sample_name',
+                            required=True, nargs='+', help='sample name')
+    the_parser.add_argument('--output', action="store",
+                            type=str, help='output tabular file')
     args = the_parser.parse_args()
     return args
 
 
-def Ref_length(bamfile):
-    """ 
-    bamfile.references: list of reference names, and bamfile.lengths is list of their lengths 
-    """
-    ref_length={}
-    for e1, e2 in zip(bamfile.references, bamfile.lengths):
-        ref_length[e1]=e2
-    return ref_length
-
-
-def Ref_coord_pol(bamfile):
-    ref_coord ={}
-    rnames =list(bamfile.references)
-    for read in bamfile:
+def compute_map_dictionary(pysam_object):
+    '''
+    returns
+    - map_dictionary {(read_chromosome,read_position,polarity):
+                     [list_of_read_length]}
+    - max_dictionary {chromosome_name:
+                      max_of_number_of_read_at_any_position}
+    '''
+    unmatched_chromosomes = list(pysam_object.references)
+    map_dictionary = defaultdict(list)
+    max_dictionary = dict.fromkeys(pysam_object.references, 0)
+    for read in pysam_object:
         if not read.is_unmapped:
-            polarity = "F" if (not read.is_reverse) else "R"
-            read_rname = read.reference_name
+            read_chromosome = read.reference_name
+            # to shift from 0-based to 1-based coordinate
             read_position = read.pos + 1
-            the_key = (read_rname, read_position,polarity)
-            read_length = read.qlen
-            try:
-                ref_coord[the_key][0] = ref_coord[the_key][0]+1
-                ref_coord[the_key][1].append(read_length)
-            except:
-                ref_coord[the_key] = [1,[read_length]]
-            if read_rname in rnames:
-                rnames.remove(read_rname)
-    for rname in rnames:
-        ref_coord[(rname, 0, "F")]=[0,[0]]
-    return collections.OrderedDict(sorted(ref_coord.items())) #dictionary {(read_rname,read_position,polarity):[nmbr_read,list_of_alignment_length]}
+            polarity = "F" if (not read.is_reverse) else "R"
+            map_dictionary[(read_chromosome, read_position,
+                            polarity)].append(read.qlen)
+            if read_chromosome in unmatched_chromosomes:
+                unmatched_chromosomes.remove(read_chromosome)
+    for name in unmatched_chromosomes:
+        # to put at least a null value by chromosome
+        map_dictionary[(name, 1, 'F')] = [0]
+    # make a dictionary with max value of reads by chromosome
+    max_dictionary = defaultdict(int)
+    for name in pysam_object.references:
+        for key in map_dictionary.keys():
+            if name in key and len(map_dictionary[key]) > max_dictionary[name]:
+                max_dictionary[name] = len(map_dictionary[key])
+    return map_dictionary, max_dictionary
 
 
-def calcul_stat(dictionary,ref):
-    dico = {}	
-    for keys in dictionary:
-        key = keys[0] #reference name
-        value = dictionary[keys][0] # position
-        try:
-            dico[key].append(value)
-        except: 
-            dico[key] = []
-            dico[key].append(value)
-    the_max = max(dico[ref])
-    return the_max
-
-
-def filename(infile): 
-    filename = basename(infile.filename)
-    the_name = filename.split('.')
-    return the_name[0]
-
-
-def main(infile, output):
-   with open(output,"w") as outfile:
-       outfile.write("Dataset" + "\t" + "Chromosome"+ "\t" + "Chrom_length" + "\t" + "Coordinate" + "\t" + "Nbr_reads" + "\t" + "Polarity" + "\t" + "Max" + "\t" + "Mean" + "\t" + "Median" + "\n")
-       for bamfile in infile:
-            with pysam.AlignmentFile(bamfile,"rb") as bamfile:
-                ref_coord = Ref_coord_pol(bamfile)
-                ref_length = Ref_length(bamfile)
-                tabulation = "\t"
-                for read in ref_coord:
-                    table = (str(filename(bamfile)), str(read[0]), str(ref_length[str(read[0])]), str(read[1]), str(ref_coord[read][0]), str(read[2]), str(calcul_stat(ref_coord,read[0])), str(round(numpy.mean(ref_coord[read][1]),1)), str(numpy.median(ref_coord[read][1])))
-                    outfile.write(tabulation.join(table) + "\n")
+def main(inputs, sample_names, output):
+    with open(output, 'w') as outfile:
+        outfile.write('\t'.join(['Dataset', 'Chromosome', 'Chrom_length',
+                                 'Coordinate', 'Nbr_reads', 'Polarity',
+                                 'Max', 'Mean', 'Median\n']))
+        chr_lengths = dict(zip(pysam.AlignmentFile(inputs[0], 'rb').references,
+                               pysam.AlignmentFile(inputs[0], 'rb').lengths))
+        for file, sample in zip(inputs, sample_names):
+            with pysam.AlignmentFile(file, 'rb') as bamfile:
+                map, maximum = compute_map_dictionary(bamfile)
+                for record in sorted(map):
+                    line = [sample, record[0],
+                            str(chr_lengths[record[0]]),
+                            str(record[1]), str(len(map[record])),
+                            record[2], str(maximum[record[0]]),
+                            str(round(numpy.mean(map[record]), 1)),
+                            str(numpy.median(map[record]))]
+                    outfile.write("\t".join(line) + "\n")
 
 
 if __name__ == "__main__":
-    args= Parser()
-    main(args.input, args.output)
+    args = Parser()
+    # if identical sample names # to be tested
+    if len(set(args.sample_name)) != len(args.sample_name):
+        args.sample_name = [name + '_' + str(i) for
+                            i, name in enumerate(args.sample_name)]
+    main(args.input, args.sample_name, args.output)
diff -r 7feee0446c5c -r 2e0dc6032a98 small_rna_map.r
--- a/small_rna_map.r	Wed Jul 12 13:40:36 2017 -0400
+++ b/small_rna_map.r	Tue Jul 18 13:34:36 2017 -0400
@@ -16,6 +16,23 @@
 theme_set(theme_bw()) #a theme with a white background
 Table = read.delim(args$output_tab, header=T, row.names=NULL)
 Table <- within(Table, Nbr_reads[Polarity=="R"] <- (Nbr_reads[Polarity=="R"]*-1))
+Chr_limits <- unique(data.frame(Dataset=Table$Dataset, Chromosome=Table$Chromosome,
+                                Chrom_length=Table$Chrom_length))
+Chr_limits_inf <- data.frame(Coordinate=Chr_limits$Chrom_length*0,
+                             Nbr_reads=Chr_limits$Chrom_length*0,
+                             Polarity=rep("F", length(Chr_limits$Dataset)),
+                             Max=Chr_limits$Chrom_length*0,
+                             Mean=Chr_limits$Chrom_length*0,
+                             Median=Chr_limits$Chrom_length*0)
+Chr_limits_inf <- cbind(Chr_limits, Chr_limits_inf)
+Chr_limits_sup <- data.frame(Coordinate=Chr_limits$Chrom_length+1,
+                             Nbr_reads=Chr_limits$Chrom_length*0,
+                             Polarity=rep("F", length(Chr_limits$Dataset)),
+                             Max=Chr_limits$Chrom_length*0,
+                             Mean=Chr_limits$Chrom_length*0,
+                             Median=Chr_limits$Chrom_length*0)
+Chr_limits_sup <- cbind(Chr_limits, Chr_limits_sup)
+Table <- rbind(Table, Chr_limits_inf, Chr_limits_sup)
  
 #To assign colors to categorical variables in ggplot2 that have stable mapping
 myColors <- brewer.pal(3,"Set1")
@@ -23,12 +40,14 @@
 colScale <- scale_colour_manual(name = "Polarity",values = myColors)
  
 #Make initial figures
+
 p <- ggplot(Table, aes(x=Coordinate, y=Nbr_reads, colour=Polarity)) +
   colScale+
-  geom_segment(aes(y = 0, x = Coordinate, yend = Nbr_reads, xend = Coordinate, color=Polarity), alpha=1) +
-  geom_segment(aes(y = Nbr_reads, x = 0, yend=Nbr_reads, xend=Chrom_length), alpha=0)+
+  geom_segment(aes(y = 0, x = Coordinate, yend = Nbr_reads, xend = Coordinate, color=Polarity)) +
+#  geom_segment(aes(y = Nbr_reads, x = 0, yend=Nbr_reads, xend=Chrom_length), alpha=0)+
   facet_wrap(Dataset~Chromosome, scales="free", nrow=1, labeller = label_wrap_gen(multi_line = FALSE))+
-  scale_y_continuous(breaks = function(x) round(pretty(seq(-(max(x) + 1), (max(x) + 1)))))+#to display only integer values on y axis
+#  scale_x_continuous(limits = c(rep(0, length(Table$Chromosome)), Chr_lengths$Chrom_length)) +
+  scale_y_continuous(breaks = function(x) round(pretty(seq(-(max(x) + 1), (max(x) + 1)))))+ # to display only integer values on y axis
   geom_hline(yintercept=0, size=0.3)+
   theme(strip.text = element_text(size = 6, lineheight = 0.1), #specify strip size
         panel.grid.major = element_line(colour = "#ffffff"),#conceal major grid lines
@@ -49,7 +68,7 @@
   scale_colour_manual(name="", values=cols)+ 
   expand_limits(y = seq(0,max(Table$Median),by=5)) +
   facet_wrap(Dataset~Chromosome, scales="free", nrow=1, labeller = label_wrap_gen(multi_line = FALSE))+
-  geom_segment(aes(y = Nbr_reads, x = 0, yend=Nbr_reads, xend=Chrom_length), alpha=0)+
+#  geom_segment(aes(y = Nbr_reads, x = 0, yend=Nbr_reads, xend=Chrom_length), alpha=0)+
   scale_y_continuous(limits = c(0,max(Table$Median)), position = "left")+
   theme(strip.background = element_blank(),
         strip.text.x = element_blank(),
@@ -64,10 +83,9 @@
 # Transforme ggplot graphs on list of graphs
 plot.list1 <- by(data     = Table,
                 INDICES  = c(Table$Chromosome),
-                simplify = TRUE,
-                FUN      = function(x) {
-                  p %+% x 
-                })
+                #simplify = TRUE,
+                FUN      = function(x) {p %+% x }
+                )
  
 plot.list2 <- by(data     = Table,
                 INDICES  = c(Table$Chromosome),
@@ -75,9 +93,10 @@
                 FUN      = function(x) {
                   p2 %+% x 
                 })
- 
+
 # Plotting in multiple pages with different rows
-multi.plot<-do.call(marrangeGrob,list(grobs=rbind(plot.list1,plot.list2),ncol=1,nrow=8,top=NULL, 
+
+grobs=rbind(plot.list1,plot.list2)
+multi.plot<-do.call(marrangeGrob,list(grobs,ncol=1,nrow=8,top=NULL, 
             bottom="Coordinates(nt)", left="Number of reads / Median & Mean", right= mylegend))
-ggsave(args$output_pdf, device="pdf", plot=multi.plot, height=11.69, width=8.2)
-
+ggsave(args$output_pdf, device="pdf", plot=multi.plot, height=11.69, width=8.2)
\ No newline at end of file
diff -r 7feee0446c5c -r 2e0dc6032a98 small_rna_map.xml
--- a/small_rna_map.xml	Wed Jul 12 13:40:36 2017 -0400
+++ b/small_rna_map.xml	Tue Jul 18 13:34:36 2017 -0400
@@ -5,6 +5,7 @@
         <requirement type="package" version="0.11.2.1=py27_0">pysam</requirement>
         <requirement type="package" version="1.3.2=r3.3.1_0">r-optparse</requirement>
         <requirement type="package" version="2.2.1=r3.3.1_0">r-ggplot2</requirement>
+        <requirement type="package" version="0.6_28=r3.3.1_0">r-latticeextra</requirement>
         <requirement type="package" version="2.2.1=r3.3.1_0">r-gridextra</requirement>
   </requirements>
   <stdio>
@@ -15,12 +16,25 @@
       --input 
       #for $file in $input
             '$file'
-      #end for 
+      #end for
+      --sample_name
+      #for $sample in $input
+          '$sample.name'
+      #end for
       --output '$output_tab' &&
-      Rscript '$__tool_directory__'/small_rna_map.r --output_tab '$output_tab' --output_pdf '$output_pdf'
+      #if $R_method=='lattice':
+          Rscript '$__tool_directory__'/lattice_small_rna_map.r --output_tab '$output_tab' --output_pdf '$output_pdf'
+      #else:
+          Rscript '$__tool_directory__'/small_rna_map.r --output_tab '$output_tab' --output_pdf '$output_pdf'
+      #end if
   ]]></command>
  <inputs>
-   <param name="input" type="data" format="bam" label="Select multiple alignments to parse" multiple="True"/>                
+   <param name="input" type="data" format="bam" label="Select multiple alignments to parse" multiple="True"/>     
+    <param help="Select the R package to produce graphics" label="lattice or ggplot" name="R_method" type="select">
+                <option selected="True" value="lattice">lattice</option>
+                <option value="ggplot">ggplot</option>
+            </param>
+              
  </inputs>
 
  <outputs>
@@ -30,10 +44,29 @@
 
     <tests>
         <test>
-            <param name="input" value="input1.bam,input2.bam,input3.bam,input4.bam" ftype="bam"/>
+            <param name="input" value="input1.bam,input2.bam" ftype="bam"/>
+            <param name="R_method" value="lattice" />
+            <output file="output.tab" name="output_tab" />
+            <output file="output_lattice.pdf" name="output_pdf" />
+        </test>
+        <test>
+            <param name="input" value="input1.bam,input1.bam" ftype="bam"/>
+            <param name="R_method" value="lattice" />
+            <output file="output_doubled.tab" name="output_tab" />
+            <output file="output_lattice_doubled.pdf" name="output_pdf" />
+        </test>
+        <test>
+            <param name="input" value="input1.bam,input2.bam" ftype="bam"/>
+            <param name="R_method" value="ggplot" />
             <output file="output.tab" name="output_tab" />
             <output file="output.pdf" name="output_pdf" />
         </test>
+        <test>
+            <param name="input" value="input1.bam,input1.bam" ftype="bam"/>
+            <param name="R_method" value="ggplot" />
+            <output file="output_doubled.tab" name="output_tab" />
+            <output file="output_doubled.pdf" name="output_pdf" />
+        </test>
     </tests>
 
 
diff -r 7feee0446c5c -r 2e0dc6032a98 test-data/input3.bam
Binary file test-data/input3.bam has changed
diff -r 7feee0446c5c -r 2e0dc6032a98 test-data/input4.bam
Binary file test-data/input4.bam has changed
diff -r 7feee0446c5c -r 2e0dc6032a98 test-data/output.pdf
Binary file test-data/output.pdf has changed
diff -r 7feee0446c5c -r 2e0dc6032a98 test-data/output.tab
--- a/test-data/output.tab	Wed Jul 12 13:40:36 2017 -0400
+++ b/test-data/output.tab	Tue Jul 18 13:34:36 2017 -0400
@@ -1,1545 +1,773 @@
 Dataset	Chromosome	Chrom_length	Coordinate	Nbr_reads	Polarity	Max	Mean	Median
-dataset_1	FBtr0070911	73	1	1	F	1	23.0	23.0
-dataset_1	FBtr0070911	73	4	1	F	1	20.0	20.0
-dataset_1	FBtr0070911	73	7	1	F	1	15.0	15.0
-dataset_1	FBtr0071581	71	1	2	F	2	21.0	21.0
-dataset_1	FBtr0071581	71	4	1	F	2	24.0	24.0
-dataset_1	FBtr0071630	71	1	1	F	1	22.0	22.0
-dataset_1	FBtr0071630	71	3	1	F	1	25.0	25.0
-dataset_1	FBtr0071736	72	3	6	F	6	25.0	26.0
-dataset_1	FBtr0072445	72	1	2	F	2	18.0	18.0
-dataset_1	FBtr0072445	72	2	1	F	2	19.0	19.0
-dataset_1	FBtr0072447	72	1	3	F	3	18.0	18.0
-dataset_1	FBtr0072580	74	14	1	F	1	20.0	20.0
-dataset_1	FBtr0072580	74	35	1	F	1	19.0	19.0
-dataset_1	FBtr0072580	74	36	1	F	1	18.0	18.0
-dataset_1	FBtr0072600	72	1	1	F	1	19.0	19.0
-dataset_1	FBtr0072600	72	43	1	F	1	28.0	28.0
-dataset_1	FBtr0072683	72	1	1	F	1	25.0	25.0
-dataset_1	FBtr0072683	72	40	1	F	1	17.0	17.0
-dataset_1	FBtr0072687	72	1	1	F	1	24.0	24.0
-dataset_1	FBtr0072687	72	5	1	F	1	20.0	20.0
-dataset_1	FBtr0072687	72	29	1	F	1	23.0	23.0
-dataset_1	FBtr0072690	72	32	1	F	1	20.0	20.0
-dataset_1	FBtr0072690	72	50	1	F	1	20.0	20.0
-dataset_1	FBtr0073018	72	7	1	F	1	16.0	16.0
-dataset_1	FBtr0073018	72	22	1	F	1	18.0	18.0
-dataset_1	FBtr0073020	72	1	1	F	1	20.0	20.0
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+input2.bam	FBtr0087055	71	3	2	F	3	24.5	24.5
+input2.bam	FBtr0087055	71	4	2	F	3	22.0	22.0
+input2.bam	FBtr0087055	71	7	3	F	3	16.0	16.0
+input2.bam	FBtr0087129	72	1	1	F	1	18.0	18.0
+input2.bam	FBtr0087129	72	7	1	F	1	23.0	23.0
+input2.bam	FBtr0087197	72	1	2	F	2	24.5	24.5
+input2.bam	FBtr0087197	72	4	2	F	2	26.0	26.0
+input2.bam	FBtr0087197	72	43	1	F	2	27.0	27.0
+input2.bam	FBtr0087198	72	15	1	F	1	16.0	16.0
+input2.bam	FBtr0087198	72	30	1	F	1	21.0	21.0
+input2.bam	FBtr0087688	73	12	2	F	2	16.0	16.0
+input2.bam	FBtr0087688	73	15	1	F	2	16.0	16.0
+input2.bam	FBtr0087961	72	5	1	F	1	24.0	24.0
+input2.bam	FBtr0087961	72	10	1	F	1	18.0	18.0
+input2.bam	FBtr0087962	72	3	1	F	1	26.0	26.0
+input2.bam	FBtr0087962	72	28	1	F	1	17.0	17.0
+input2.bam	FBtr0088087	73	1	1	F	1	18.0	18.0
+input2.bam	FBtr0088087	73	42	1	F	1	15.0	15.0
+input2.bam	FBtr0088156	87	6	1	F	1	18.0	18.0
+input2.bam	FBtr0088156	87	8	1	F	1	19.0	19.0
+input2.bam	FBtr0088156	87	41	1	F	1	18.0	18.0
+input2.bam	FBtr0089302	83	1	1	F	1	19.0	19.0
+input2.bam	FBtr0089302	83	12	1	F	1	16.0	16.0
+input2.bam	FBtr0089302	83	45	1	F	1	20.0	20.0
+input2.bam	FBtr0089613	71	1	4	F	4	23.3	22.5
+input2.bam	FBtr0089613	71	3	3	F	4	22.7	23.0
+input2.bam	FBtr0089613	71	19	1	F	4	22.0	22.0
+input2.bam	FBtr0089613	71	51	1	F	4	18.0	18.0
+input2.bam	FBtr0100842	73	1	28	F	28	22.0	22.0
+input2.bam	FBtr0100843	72	1	1	F	1	26.0	26.0
+input2.bam	FBtr0100843	72	4	1	F	1	26.0	26.0
+input2.bam	FBtr0100843	72	32	1	F	1	22.0	22.0
+input2.bam	FBtr0100845	84	11	1	F	1	15.0	15.0
+input2.bam	FBtr0100845	84	12	1	F	1	15.0	15.0
+input2.bam	FBtr0100846	73	16	1	F	1	16.0	16.0
+input2.bam	FBtr0100846	73	42	1	F	1	21.0	21.0
+input2.bam	FBtr0100847	72	28	1	F	1	23.0	23.0
+input2.bam	FBtr0100847	72	53	1	F	1	16.0	16.0
+input2.bam	FBtr0100854	65	1	14	F	14	18.8	20.0
+input2.bam	FBtr0100854	65	2	1	F	14	19.0	19.0
+input2.bam	FBtr0100854	65	19	1	F	14	21.0	21.0
+input2.bam	FBtr0100856	69	33	1	F	1	17.0	17.0
+input2.bam	FBtr0100856	69	47	1	F	1	18.0	18.0
+input2.bam	FBtr0100858	66	1	1	F	1	22.0	22.0
+input2.bam	FBtr0100858	66	3	1	F	1	17.0	17.0
+input2.bam	FBtr0100859	62	1	1	F	2	16.0	16.0
+input2.bam	FBtr0100859	62	5	1	F	2	16.0	16.0
+input2.bam	FBtr0100859	62	16	1	F	2	17.0	17.0
+input2.bam	FBtr0100859	62	29	1	F	2	18.0	18.0
+input2.bam	FBtr0100859	62	45	2	F	2	17.0	17.0
+input2.bam	FBtr0100860	66	1	1	F	2	17.0	17.0
+input2.bam	FBtr0100860	66	7	1	F	2	17.0	17.0
+input2.bam	FBtr0100860	66	11	1	F	2	17.0	17.0
+input2.bam	FBtr0100860	66	13	1	F	2	18.0	18.0
+input2.bam	FBtr0100860	66	18	2	F	2	17.0	17.0
+input2.bam	FBtr0100860	66	20	1	F	2	15.0	15.0
+input2.bam	FBtr0100860	66	46	1	F	2	17.0	17.0
+input2.bam	FBtr0100862	66	1	2	F	4	16.5	16.5
+input2.bam	FBtr0100862	66	6	2	F	4	20.0	20.0
+input2.bam	FBtr0100862	66	22	1	F	4	19.0	19.0
+input2.bam	FBtr0100862	66	44	4	F	4	20.0	20.0
+input2.bam	FBtr0100862	66	46	1	F	4	18.0	18.0
+input2.bam	FBtr0100862	66	48	2	F	4	18.5	18.5
+input2.bam	FBtr0100862	66	49	1	F	4	18.0	18.0
+input2.bam	FBtr0100864	71	1	8	F	8	18.5	18.0
+input2.bam	FBtr0100864	71	3	1	F	8	23.0	23.0
+input2.bam	FBtr0100864	71	8	1	F	8	18.0	18.0
+input2.bam	FBtr0100864	71	10	1	F	8	22.0	22.0
+input2.bam	FBtr0100864	71	11	1	F	8	20.0	20.0
+input2.bam	FBtr0100864	71	12	2	F	8	21.5	21.5
+input2.bam	FBtr0100864	71	13	1	F	8	24.0	24.0
+input2.bam	FBtr0100864	71	14	1	F	8	20.0	20.0
+input2.bam	FBtr0100864	71	15	3	F	8	19.7	21.0
+input2.bam	FBtr0100864	71	16	2	F	8	20.5	20.5
+input2.bam	FBtr0100864	71	19	1	F	8	18.0	18.0
+input2.bam	FBtr0100864	71	21	2	F	8	17.0	17.0
+input2.bam	FBtr0100864	71	44	2	F	8	16.0	16.0
+input2.bam	FBtr0100864	71	51	1	F	8	21.0	21.0
+input2.bam	FBtr0100864	71	56	1	F	8	16.0	16.0
+input2.bam	FBtr0100865	67	1	1	F	1	16.0	16.0
+input2.bam	FBtr0100865	67	19	1	F	1	19.0	19.0
+input2.bam	FBtr0100865	67	20	1	F	1	20.0	20.0
+input2.bam	FBtr0100865	67	23	1	F	1	17.0	17.0
+input2.bam	FBtr0100869	65	1	3	F	3	18.3	19.0
+input2.bam	FBtr0100869	65	12	1	F	3	16.0	16.0
+input2.bam	FBtr0100869	65	16	1	F	3	17.0	17.0
+input2.bam	FBtr0100869	65	17	1	F	3	20.0	20.0
+input2.bam	FBtr0100869	65	28	1	F	3	16.0	16.0
+input2.bam	FBtr0100869	65	30	2	F	3	20.5	20.5
+input2.bam	FBtr0100869	65	33	2	F	3	19.5	19.5
+input2.bam	FBtr0100869	65	36	1	F	3	18.0	18.0
+input2.bam	FBtr0100871	65	1	22	F	22	17.1	17.0
+input2.bam	FBtr0100871	65	15	1	F	22	23.0	23.0
+input2.bam	FBtr0100871	65	27	1	F	22	16.0	16.0
+input2.bam	FBtr0100872	64	1	49	F	49	18.8	18.0
+input2.bam	FBtr0100872	64	2	1	F	49	17.0	17.0
+input2.bam	FBtr0100872	64	5	1	F	49	18.0	18.0
+input2.bam	FBtr0100872	64	6	2	F	49	17.0	17.0
+input2.bam	FBtr0100872	64	7	3	F	49	17.3	16.0
+input2.bam	FBtr0100872	64	8	1	F	49	19.0	19.0
+input2.bam	FBtr0100872	64	9	2	F	49	19.5	19.5
+input2.bam	FBtr0100872	64	10	2	F	49	20.0	20.0
+input2.bam	FBtr0100872	64	11	1	F	49	16.0	16.0
+input2.bam	FBtr0100872	64	13	1	F	49	16.0	16.0
+input2.bam	FBtr0100872	64	15	5	F	49	22.0	22.0
+input2.bam	FBtr0100872	64	16	2	F	49	21.0	21.0
+input2.bam	FBtr0100872	64	18	2	F	49	19.5	19.5
+input2.bam	FBtr0100872	64	19	9	F	49	18.2	18.0
+input2.bam	FBtr0100872	64	22	3	F	49	16.0	16.0
+input2.bam	FBtr0100872	64	36	2	F	49	16.0	16.0
+input2.bam	FBtr0100872	64	42	1	F	49	18.0	18.0
+input2.bam	FBtr0100874	68	1	83	F	83	19.5	19.0
+input2.bam	FBtr0100874	68	3	4	F	83	17.3	17.0
+input2.bam	FBtr0100874	68	4	1	F	83	18.0	18.0
+input2.bam	FBtr0100874	68	5	1	F	83	17.0	17.0
+input2.bam	FBtr0100874	68	10	1	F	83	16.0	16.0
+input2.bam	FBtr0100874	68	13	1	F	83	23.0	23.0
+input2.bam	FBtr0100874	68	20	1	F	83	20.0	20.0
+input2.bam	FBtr0100875	67	3	1	F	1	18.0	18.0
+input2.bam	FBtr0100875	67	26	1	F	1	16.0	16.0
+input2.bam	FBtr0100875	67	48	1	F	1	16.0	16.0
+input2.bam	FBtr0100876	65	1	1	F	2	27.0	27.0
+input2.bam	FBtr0100876	65	6	1	F	2	16.0	16.0
+input2.bam	FBtr0100876	65	9	1	F	2	19.0	19.0
+input2.bam	FBtr0100876	65	13	2	F	2	15.5	15.5
+input2.bam	FBtr0100876	65	18	1	F	2	19.0	19.0
+input2.bam	FBtr0100876	65	19	1	F	2	18.0	18.0
+input2.bam	FBtr0100876	65	28	1	F	2	17.0	17.0
+input2.bam	FBtr0100876	65	29	1	F	2	19.0	19.0
+input2.bam	FBtr0100876	65	48	1	F	2	16.0	16.0
+input2.bam	FBtr0100878	66	23	1	F	3	21.0	21.0
+input2.bam	FBtr0100878	66	26	1	F	3	16.0	16.0
+input2.bam	FBtr0100878	66	27	1	F	3	15.0	15.0
+input2.bam	FBtr0100878	66	28	3	F	3	18.3	18.0
+input2.bam	FBtr0100878	66	30	2	F	3	20.0	20.0
+input2.bam	FBtr0100878	66	34	2	F	3	18.0	18.0
+input2.bam	FBtr0100878	66	35	1	F	3	15.0	15.0
+input2.bam	FBtr0100885	66	20	1	F	2	23.0	23.0
+input2.bam	FBtr0100885	66	46	2	F	2	17.0	17.0
+input2.bam	FBtr0100885	66	47	1	F	2	16.0	16.0
+input2.bam	FBtr0100887	65	1	1	F	1	21.0	21.0
+input2.bam	FBtr0100887	65	5	1	F	1	21.0	21.0
+input2.bam	FBtr0100887	65	6	1	F	1	20.0	20.0
+input2.bam	FBtr0100887	65	39	1	F	1	21.0	21.0
+input2.bam	FBtr0100889	73	3	1	F	1	19.0	19.0
+input2.bam	FBtr0100889	73	15	1	F	1	17.0	17.0
+input2.bam	FBtr0100889	73	23	1	F	1	20.0	20.0
+input2.bam	FBtr0100889	73	24	1	F	1	23.0	23.0
+input2.bam	FBtr0100889	73	27	1	F	1	15.0	15.0
+input2.bam	FBtr0100889	73	37	1	F	1	20.0	20.0
+input2.bam	FBtr0100889	73	42	1	F	1	17.0	17.0
+input2.bam	FBtr0100889	73	48	1	F	1	19.0	19.0
diff -r 7feee0446c5c -r 2e0dc6032a98 test-data/output_doubled.pdf
Binary file test-data/output_doubled.pdf has changed
diff -r 7feee0446c5c -r 2e0dc6032a98 test-data/output_doubled.tab
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output_doubled.tab	Tue Jul 18 13:34:36 2017 -0400
@@ -0,0 +1,773 @@
+Dataset	Chromosome	Chrom_length	Coordinate	Nbr_reads	Polarity	Max	Mean	Median
+input1.bam_0	FBtr0070911	73	1	1	F	1	23.0	23.0
+input1.bam_0	FBtr0070911	73	4	1	F	1	20.0	20.0
+input1.bam_0	FBtr0070911	73	7	1	F	1	15.0	15.0
+input1.bam_0	FBtr0071581	71	1	2	F	2	21.0	21.0
+input1.bam_0	FBtr0071581	71	4	1	F	2	24.0	24.0
+input1.bam_0	FBtr0071630	71	1	1	F	1	22.0	22.0
+input1.bam_0	FBtr0071630	71	3	1	F	1	25.0	25.0
+input1.bam_0	FBtr0071736	72	3	6	F	6	25.0	26.0
+input1.bam_0	FBtr0072445	72	1	2	F	2	18.0	18.0
+input1.bam_0	FBtr0072445	72	2	1	F	2	19.0	19.0
+input1.bam_0	FBtr0072447	72	1	3	F	3	18.0	18.0
+input1.bam_0	FBtr0072580	74	14	1	F	1	20.0	20.0
+input1.bam_0	FBtr0072580	74	35	1	F	1	19.0	19.0
+input1.bam_0	FBtr0072580	74	36	1	F	1	18.0	18.0
+input1.bam_0	FBtr0072600	72	1	1	F	1	19.0	19.0
+input1.bam_0	FBtr0072600	72	43	1	F	1	28.0	28.0
+input1.bam_0	FBtr0072683	72	1	1	F	1	25.0	25.0
+input1.bam_0	FBtr0072683	72	40	1	F	1	17.0	17.0
+input1.bam_0	FBtr0072687	72	1	1	F	1	24.0	24.0
+input1.bam_0	FBtr0072687	72	5	1	F	1	20.0	20.0
+input1.bam_0	FBtr0072687	72	29	1	F	1	23.0	23.0
+input1.bam_0	FBtr0072690	72	32	1	F	1	20.0	20.0
+input1.bam_0	FBtr0072690	72	50	1	F	1	20.0	20.0
+input1.bam_0	FBtr0073018	72	7	1	F	1	16.0	16.0
+input1.bam_0	FBtr0073018	72	22	1	F	1	18.0	18.0
+input1.bam_0	FBtr0073020	72	1	1	F	1	20.0	20.0
+input1.bam_0	FBtr0073020	72	29	1	F	1	22.0	22.0
+input1.bam_0	FBtr0073125	73	1	1	F	1	29.0	29.0
+input1.bam_0	FBtr0073125	73	15	1	F	1	17.0	17.0
+input1.bam_0	FBtr0073125	73	16	1	F	1	19.0	19.0
+input1.bam_0	FBtr0073125	73	32	1	F	1	21.0	21.0
+input1.bam_0	FBtr0073857	73	1	1	F	1	19.0	19.0
+input1.bam_0	FBtr0073857	73	44	1	F	1	17.0	17.0
+input1.bam_0	FBtr0073861	73	30	1	F	1	22.0	22.0
+input1.bam_0	FBtr0073861	73	52	1	F	1	20.0	20.0
+input1.bam_0	FBtr0073865	82	1	1	F	1	25.0	25.0
+input1.bam_0	FBtr0073865	82	49	1	F	1	16.0	16.0
+input1.bam_0	FBtr0073866	82	1	1	F	1	24.0	24.0
+input1.bam_0	FBtr0073866	82	3	1	F	1	22.0	22.0
+input1.bam_0	FBtr0073872	82	1	1	F	1	18.0	18.0
+input1.bam_0	FBtr0073872	82	4	1	F	1	22.0	22.0
+input1.bam_0	FBtr0073872	82	44	1	F	1	20.0	20.0
+input1.bam_0	FBtr0073872	82	48	1	F	1	16.0	16.0
+input1.bam_0	FBtr0073885	82	1	2	F	2	25.0	25.0
+input1.bam_0	FBtr0073886	82	1	4	F	4	24.0	24.0
+input1.bam_0	FBtr0075244	72	1	1	F	1	19.0	19.0
+input1.bam_0	FBtr0075244	72	3	1	F	1	23.0	23.0
+input1.bam_0	FBtr0075244	72	8	1	F	1	20.0	20.0
+input1.bam_0	FBtr0075244	72	10	1	F	1	19.0	19.0
+input1.bam_0	FBtr0075681	72	1	1	F	1	19.0	19.0
+input1.bam_0	FBtr0075681	72	41	1	F	1	20.0	20.0
+input1.bam_0	FBtr0075713	72	41	1	F	1	19.0	19.0
+input1.bam_0	FBtr0075713	72	42	1	F	1	18.0	18.0
+input1.bam_0	FBtr0075713	72	43	1	F	1	16.0	16.0
+input1.bam_0	FBtr0075830	72	1	2	F	2	17.5	17.5
+input1.bam_0	FBtr0075830	72	15	1	F	2	23.0	23.0
+input1.bam_0	FBtr0076083	72	1	1	F	1	18.0	18.0
+input1.bam_0	FBtr0076083	72	33	1	F	1	21.0	21.0
+input1.bam_0	FBtr0076743	83	1	3	F	3	16.7	16.0
+input1.bam_0	FBtr0076743	83	7	1	F	3	20.0	20.0
+input1.bam_0	FBtr0076743	83	34	1	F	3	16.0	16.0
+input1.bam_0	FBtr0076743	83	45	1	F	3	21.0	21.0
+input1.bam_0	FBtr0076762	73	1	31	F	31	22.1	22.0
+input1.bam_0	FBtr0076762	73	3	1	F	31	20.0	20.0
+input1.bam_0	FBtr0077142	82	1	4	F	4	23.5	24.0
+input1.bam_0	FBtr0077142	82	3	1	F	4	21.0	21.0
+input1.bam_0	FBtr0077142	82	49	1	F	4	15.0	15.0
+input1.bam_0	FBtr0077143	73	41	1	F	3	22.0	22.0
+input1.bam_0	FBtr0077143	73	44	1	F	3	22.0	22.0
+input1.bam_0	FBtr0077143	73	45	3	F	3	17.3	16.0
+input1.bam_0	FBtr0077158	73	44	1	F	3	22.0	22.0
+input1.bam_0	FBtr0077158	73	46	3	F	3	18.7	20.0
+input1.bam_0	FBtr0077458	72	33	1	F	1	21.0	21.0
+input1.bam_0	FBtr0077458	72	35	1	F	1	20.0	20.0
+input1.bam_0	FBtr0077577	82	1	2	F	2	25.0	25.0
+input1.bam_0	FBtr0077577	82	55	1	F	2	18.0	18.0
+input1.bam_0	FBtr0077577	82	62	1	F	2	18.0	18.0
+input1.bam_0	FBtr0077613	82	1	5	F	5	24.6	25.0
+input1.bam_0	FBtr0077821	71	1	4	F	4	20.3	22.0
+input1.bam_0	FBtr0077821	71	3	2	F	4	25.0	25.0
+input1.bam_0	FBtr0077821	71	4	1	F	4	24.0	24.0
+input1.bam_0	FBtr0077821	71	18	1	F	4	23.0	23.0
+input1.bam_0	FBtr0077821	71	33	1	F	4	20.0	20.0
+input1.bam_0	FBtr0077872	71	1	3	F	4	22.7	23.0
+input1.bam_0	FBtr0077872	71	3	4	F	4	23.8	25.0
+input1.bam_0	FBtr0077872	71	4	1	F	4	19.0	19.0
+input1.bam_0	FBtr0077872	71	7	1	F	4	16.0	16.0
+input1.bam_0	FBtr0077872	71	18	2	F	4	21.0	21.0
+input1.bam_0	FBtr0078547	83	1	1	F	1	16.0	16.0
+input1.bam_0	FBtr0078547	83	50	1	F	1	15.0	15.0
+input1.bam_0	FBtr0079090	72	52	2	F	2	18.0	18.0
+input1.bam_0	FBtr0079528	71	1	3	F	3	22.3	22.0
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diff -r 7feee0446c5c -r 2e0dc6032a98 test-data/output_lattice.pdf
Binary file test-data/output_lattice.pdf has changed
diff -r 7feee0446c5c -r 2e0dc6032a98 test-data/output_lattice_doubled.pdf
Binary file test-data/output_lattice_doubled.pdf has changed