# HG changeset patch
# User artbio
# Date 1500892125 14400
# Node ID 6d48150495e3776ef3d00377dc0532217a1d4ddf

planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959

diff -r 000000000000 -r 6d48150495e3 small_rna_maps.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/small_rna_maps.py	Mon Jul 24 06:28:45 2017 -0400
@@ -0,0 +1,204 @@
+import argparse
+from collections import defaultdict
+
+import numpy
+
+import pysam
+
+
+def Parser():
+    the_parser = argparse.ArgumentParser()
+    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')
+    the_parser.add_argument('-S', '--sizes', action='store',
+                            help='use to output read sizes dataframe')
+    args = the_parser.parse_args()
+    return args
+
+
+class Map:
+
+    def __init__(self, bam_file, sample, computeSize=False):
+        self.sample_name = sample
+        self.bam_object = pysam.AlignmentFile(bam_file, 'rb')
+        self.chromosomes = dict(zip(self.bam_object.references,
+                                self.bam_object.lengths))
+        self.map_dict = self.create_map(self.bam_object)
+        self.max = self.compute_max(self.map_dict)
+        self.mean = self.compute_mean(self.map_dict)
+        self.median = self.compute_median(self.map_dict)
+        self.coverage = self.compute_coverage(self.map_dict)
+        if computeSize:
+            self.size = self.compute_size(self.map_dict)
+
+    def create_map(self, bam_object):
+        '''
+        Returns a map_dictionary {(chromosome,read_position,polarity):
+                                                    [read_length, ...]}
+        '''
+        map_dictionary = defaultdict(list)
+        # get empty value for start and end of each chromosome
+        for chrom in self.chromosomes:
+            map_dictionary[(chrom, 1, 'F')] = []
+            map_dictionary[(chrom, self.chromosomes[chrom], 'F')] = []
+        for chrom in self.chromosomes:
+            for read in bam_object.fetch(chrom):
+                positions = read.positions  # a list of covered positions
+                for pos in positions:
+                    if not map_dictionary[(chrom, pos+1, 'F')]:
+                        map_dictionary[(chrom, pos+1, 'F')] = []
+                    if not map_dictionary[(chrom, pos+1, 'R')]:
+                        map_dictionary[(chrom, pos+1, 'R')] = []
+                if read.is_reverse:
+                    map_dictionary[(chrom, positions[-1]+1,
+                                    'R')].append(read.query_alignment_length)
+                else:
+                    map_dictionary[(chrom, positions[0]+1,
+                                    'F')].append(read.query_alignment_length)
+        return map_dictionary
+
+    def compute_max(self, map_dictionary):
+        '''
+        takes a map_dictionary as input and returns
+        a max_dictionary {(chromosome,read_position,polarity):
+                              max_of_number_of_read_at_any_position}
+        '''
+        merge_keylist = [(i[0], 0) for i in map_dictionary.keys()]
+        max_dictionary = dict(merge_keylist)
+        for key in map_dictionary:
+            if len(map_dictionary[key]) > max_dictionary[key[0]]:
+                max_dictionary[key[0]] = len(map_dictionary[key])
+        return max_dictionary
+
+    def compute_mean(self, map_dictionary):
+        '''
+        takes a map_dictionary as input and returns
+        a mean_dictionary {(chromosome,read_position,polarity):
+                                                mean_value_of_reads}
+        '''
+        mean_dictionary = dict()
+        for key in map_dictionary:
+            if len(map_dictionary[key]) == 0:
+                mean_dictionary[key] = 0
+            else:
+                mean_dictionary[key] = round(numpy.mean(map_dictionary[key]),
+                                             1)
+        return mean_dictionary
+
+    def compute_median(self, map_dictionary):
+        '''
+        takes a map_dictionary as input and returns
+        a mean_dictionary {(chromosome,read_position,polarity):
+                                                    mean_value_of_reads}
+        '''
+        median_dictionary = dict()
+        for key in map_dictionary:
+            if len(map_dictionary[key]) == 0:
+                median_dictionary[key] = 0
+            else:
+                median_dictionary[key] = numpy.median(map_dictionary[key])
+        return median_dictionary
+
+    def compute_coverage(self, map_dictionary, quality=10):
+        '''
+        takes a map_dictionary as input and returns
+        a coverage_dictionary {(chromosome,read_position,polarity):
+                                                coverage}
+        '''
+        coverage_dictionary = dict()
+        for chrom in self.chromosomes:
+            coverage_dictionary[(chrom, 1, 'F')] = 0
+            coverage_dictionary[(chrom, self.chromosomes[chrom], 'F')] = 0
+
+        for key in map_dictionary:
+            coverage = self.bam_object.count_coverage(
+                                                reference=key[0],
+                                                start=key[1]-1,
+                                                end=key[1],
+                                                quality_threshold=quality)
+            """ Add the 4 coverage values """
+            coverage = [sum(x) for x in zip(*coverage)]
+            coverage_dictionary[key] = coverage[0]
+            # coverage_dictionary[(key[0], key[1], 'R')] = coverage
+        return coverage_dictionary
+
+    def compute_size(self, map_dictionary):
+        '''
+        Takes a map_dictionary and returns a dictionary of sizes:
+        {chrom: {polarity: {size: nbre of reads}}}
+        '''
+        size_dictionary = defaultdict(lambda: defaultdict(
+                                      lambda: defaultdict( int )))
+        #  to track empty chromosomes
+        for chrom in self.chromosomes:
+            if self.bam_object.count(chrom) == 0:
+                size_dictionary[chrom]['F'][10] = 0
+        for key in map_dictionary:
+            for size in map_dictionary[key]:
+                size_dictionary[key[0]][key[2]][size] += 1
+        return size_dictionary
+
+    def write_size_table(self, out):
+        '''
+        Dataset, Chromosome, Polarity, Size, Nbr_reads
+        out is an *open* file handler
+        '''
+        for chrom in sorted(self.size):
+            sizes = self.size[chrom]['F'].keys()
+            sizes.extend(self.size[chrom]['R'].keys())
+            for polarity in sorted(self.size[chrom]):
+                for size in range(min(sizes), max(sizes)+1):
+                    try:
+                        line = [self.sample_name, chrom, polarity, size,
+                                self.size[chrom][polarity][size]]
+                    except KeyError:
+                        line = [self.sample_name, chrom, polarity, size, 0]
+                    line = [str(i) for i in line]
+                    out.write('\t'.join(line) + '\n')
+
+    def write_table(self, out):
+        '''
+        Dataset, Chromosome, Chrom_length, Coordinate, Nbr_reads
+        Polarity, Max, Mean, Median, Coverage
+        out is an *open* file handler
+        '''
+        for key in sorted(self.map_dict):
+            line = [self.sample_name, key[0], self.chromosomes[key[0]],
+                    key[1], len(self.map_dict[key]), key[2], self.max[key[0]],
+                    self.mean[key], self.median[key], self.coverage[key]]
+            line = [str(i) for i in line]
+            out.write('\t'.join(line) + '\n')
+
+
+def main(inputs, samples, file_out, size_file_out=''):
+    F = open(file_out, 'w')
+    header = ["Dataset", "Chromosome", "Chrom_length", "Coordinate",
+              "Nbr_reads", "Polarity", "Max", "Mean", "Median", "Coverage"]
+    F.write('\t'.join(header) + '\n')
+    if size_file_out:
+        Fs = open(size_file_out, 'w')
+        header = ["Dataset", "Chromosome", "Polarity", "Size", "Nbr_reads"]
+        Fs.write('\t'.join(header) + '\n')
+        for file, sample in zip(inputs, samples):
+            mapobj = Map(file, sample, computeSize=True)
+            mapobj.write_table(F)
+            mapobj.write_size_table(Fs)
+        Fs.close()
+    else:
+        for file, sample in zip(inputs, samples):
+            mapobj = Map(file, sample, computeSize=False)
+            mapobj.write_table(F)
+        F.close()
+
+
+if __name__ == "__main__":
+    args = Parser()
+    # if identical sample names
+    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, args.sizes)
diff -r 000000000000 -r 6d48150495e3 small_rna_maps.r
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/small_rna_maps.r	Mon Jul 24 06:28:45 2017 -0400
@@ -0,0 +1,141 @@
+## 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(c("-s", "--sizes"), type="character", help="path to size dataframe"),
+    make_option("--output_pdf", type = "character", help="path to the pdf file with plot"),
+    make_option("--extra_plot", type = "character", help="what additional data should be plotted")
+    )
+ 
+parser <- OptionParser(usage = "%prog [options] file", option_list = option_list)
+args = parse_args(parser)
+if (length(args$sizes) != 0) { args$extra_plot <- "SizeDistribution"}
+ 
+# 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)
+if (args$extra_plot == "SizeDistribution") {
+    size=read.delim(args$sizes, header=T, row.names=NULL)
+    size <- within(size, Nbr_reads[Polarity=="R"] <- (Nbr_reads[Polarity=="R"]*-1))
+    per_gene_size=lapply(genes, function(x) subset(size, Chromosome==x))
+    }
+
+## 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',
+    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),
+    ...))
+    }
+
+
+plot_size=function(df, ...) {
+    #smR.prepanel=function(x,y,...) {; yscale=c(y*0, max(abs(y)));list(ylim=yscale);}
+    sizeplot = xyplot(eval(as.name(args$extra_plot))~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),
+    ...)
+    combineLimits(sizeplot)
+    }
+
+plot_size_distribution= function(df, ...) {
+#  smR.prepanel=function(x,y,...){; yscale=c(-max(abs(y)), max(abs(y)));list(ylim=yscale);}
+  bc= barchart(Nbr_reads~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) ),
+#    prepanel=smR.prepanel,
+    xlab = NULL,
+    ylab = NULL,
+    main = NULL,
+    as.table=TRUE,
+    newpage = T,
+    par.strip.text = list(cex=0.7),
+    ...)
+  combineLimits(bc)
+  }
+
+
+## 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))
+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", SizeDistribution="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}
+    readmap_plot.list=lapply(per_gene_readmap[start:end], function(x) plot_readmap(x, strip=FALSE, par.settings=par.settings.readmap))
+    if (args$extra_plot == "SizeDistribution") {
+        size_plot.list=lapply(per_gene_size[start:end], function(x) plot_size_distribution(x, par.settings=par.settings.size))
+        }
+    else {
+        size_plot.list=lapply(per_gene_readmap[start:end], function(x) plot_size(x, par.settings=par.settings.size))
+        }
+    
+        
+    plot.list=rbind(size_plot.list, readmap_plot.list)
+    args_list=c(plot.list, list(nrow=rows_per_page+1, ncol=1,
+                                    top=textGrob(graph_title[[args$extra_plot]], gp=gpar(cex=1), just="top"),
+                                    left=textGrob(graph_legend[[args$extra_plot]], gp=gpar(cex=1), vjust=1, rot=90),
+                                    sub=textGrob(graph_bottom[[args$extra_plot]], gp=gpar(cex=1), just="bottom")
+                                    )
+           )
+do.call(grid.arrange, args_list)
+}
+devname=dev.off()
+
diff -r 000000000000 -r 6d48150495e3 small_rna_maps.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/small_rna_maps.xml	Mon Jul 24 06:28:45 2017 -0400
@@ -0,0 +1,129 @@
+<tool id="small_rna_maps" name="small_rna_maps" version="0.9.0">
+  <description></description>
+  <requirements>
+        <requirement type="package" version="1.11.2=py27_0">numpy</requirement>
+        <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="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>
+      <exit_code range="1:" level="fatal" description="Tool exception" />
+  </stdio>
+  <command detect_errors="exit_code"><![CDATA[
+      #for $file in $input
+          samtools index '$file' &&
+      #end for
+      python '$__tool_directory__'/small_rna_maps.py 
+      --input 
+      #for $file in $input
+           '$file'
+      #end for
+          --sample_name
+      #for $sample in $input
+          '$sample.name'
+      #end for
+      #if $extra_plot == 'Sizes':
+          --sizes '$output_sizes'
+      #end if
+      --output '$output_tab' &&
+       Rscript '$__tool_directory__'/small_rna_maps.r --output_tab '$output_tab' 
+               --output_pdf '$output_pdf'
+      #if $extra_plot != 'Sizes':
+          --extra_plot '$extra_plot'
+      #else
+          --sizes $output_sizes
+      #end if
+  ]]></command>
+ <inputs>
+   <param name="input" type="data" format="bam" label="Select multiple alignments to parse" multiple="True"/> 
+   <param name="extra_plot" type="select" label="select the type of extra plot in addition to read map">
+       <option value="Coverage">Coverage</option> 
+       <option value="Mean">Mean Sizes</option> 
+       <option value="Median">Median Sizes</option>
+       <option value="Sizes">Size Distributions</option>
+    </param>
+ </inputs>
+
+ <outputs>
+   <data format="tabular" name="output_tab" label="Map dataframe" />
+   <data format="tabular" name="output_sizes" label="Size dataframe" >
+       <filter>extra_plot == "Sizes"</filter>
+   </data>
+   <data format="pdf" name="output_pdf" label="PDF file" />
+
+</outputs>
+
+    <tests>
+        <test>
+            <param name="input" value="input1.bam,input2.bam" ftype="bam"/>
+            <param name="extra_plot" value="Mean" />
+            <output file="output.tab" name="output_tab" />
+            <output file="mean.pdf" name="output_pdf" />
+        </test>
+        <test>
+            <param name="input" value="input1.bam,input1.bam" ftype="bam"/>
+            <param name="extra_plot" value="Mean" />
+            <output file="doubled.tab" name="output_tab" />
+            <output file="doubled_mean.pdf" name="output_pdf" />
+        </test>
+        <test>
+            <param name="input" value="input1.bam,input2.bam" ftype="bam"/>
+            <param name="extra_plot" value="Median" />
+            <output file="output.tab" name="output_tab" />
+            <output file="median.pdf" name="output_pdf" />
+        </test>
+        <test>
+            <param name="input" value="input1.bam,input2.bam" ftype="bam"/>
+            <param name="extra_plot" value="Coverage" />
+            <output file="output.tab" name="output_tab" />
+            <output file="coverage.pdf" name="output_pdf" />
+        </test>
+        <test>
+            <param name="input" value="input1.bam,input2.bam" ftype="bam"/>
+            <param name="extra_plot" value="Sizes" />
+            <output file="output.tab" name="output_tab" />
+            <output file="sizes.tab" name="output_sizes" />
+            <output file="sizes.pdf" name="output_pdf" />
+        </test>
+    </tests>
+
+
+<help>
+
+**What it does**
+
+Generate read count maps from alignment BAM files, using pysam and lattice.
+
+In addition to the read counts (lower graphs), median size, mean size and coverage depth of reads(lower graphs) mapping at a given position are plotted.	
+
+**Inputs**
+
+bam alignment files that *must* be
+
+  - single-read
+  - sorted
+  - mapping to the same reference
+
+**Output**
+
+A pdf file generated by the R package lattice
+
+One or two dataframes used to plot data
+
+</help>
+
+<citations>
+    <citation type="doi">10.1093/bioinformatics/btp352</citation>
+     <citation type="bibtex">@Book{,
+    title = {Lattice: Multivariate Data Visualization with R},
+    author = {Deepayan Sarkar},
+    publisher = {Springer},
+    address = {New York},
+    year = {2008},
+    note = {ISBN 978-0-387-75968-5},
+    url = {http://lmdvr.r-forge.r-project.org},
+  }</citation>
+</citations>
+</tool>
+
diff -r 000000000000 -r 6d48150495e3 test-data/coverage.pdf
Binary file test-data/coverage.pdf has changed
diff -r 000000000000 -r 6d48150495e3 test-data/doubled.tab
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/doubled.tab	Mon Jul 24 06:28:45 2017 -0400
@@ -0,0 +1,6339 @@
+Dataset	Chromosome	Chrom_length	Coordinate	Nbr_reads	Polarity	Max	Mean	Median	Coverage
+input1.bam_0	FBtr0070001	72	1	1	F	27	17.0	17.0	1
+input1.bam_0	FBtr0070001	72	1	0	R	27	0	0	1
+input1.bam_0	FBtr0070001	72	2	0	F	27	0	0	1
+input1.bam_0	FBtr0070001	72	2	0	R	27	0	0	1
+input1.bam_0	FBtr0070001	72	3	0	F	27	0	0	1
+input1.bam_0	FBtr0070001	72	3	0	R	27	0	0	1
+input1.bam_0	FBtr0070001	72	4	0	F	27	0	0	1
+input1.bam_0	FBtr0070001	72	4	0	R	27	0	0	1
+input1.bam_0	FBtr0070001	72	5	0	F	27	0	0	1
+input1.bam_0	FBtr0070001	72	5	0	R	27	0	0	1
+input1.bam_0	FBtr0070001	72	6	0	F	27	0	0	1
+input1.bam_0	FBtr0070001	72	6	0	R	27	0	0	1
+input1.bam_0	FBtr0070001	72	7	6	F	27	20.3	21.0	7
+input1.bam_0	FBtr0070001	72	7	0	R	27	0	0	7
+input1.bam_0	FBtr0070001	72	8	3	F	27	21.3	21.0	10
+input1.bam_0	FBtr0070001	72	8	0	R	27	0	0	10
+input1.bam_0	FBtr0070001	72	9	0	F	27	0	0	10
+input1.bam_0	FBtr0070001	72	9	0	R	27	0	0	10
+input1.bam_0	FBtr0070001	72	10	0	F	27	0	0	10
+input1.bam_0	FBtr0070001	72	10	0	R	27	0	0	10
+input1.bam_0	FBtr0070001	72	11	2	F	27	20.5	20.5	12
+input1.bam_0	FBtr0070001	72	11	0	R	27	0	0	12
+input1.bam_0	FBtr0070001	72	12	0	F	27	0	0	12
+input1.bam_0	FBtr0070001	72	12	0	R	27	0	0	12
+input1.bam_0	FBtr0070001	72	13	0	F	27	0	0	12
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+input1.bam_1	FBtr0080664	71	70	0	F	56	0	0	1
+input1.bam_1	FBtr0080664	71	70	0	R	56	0	0	1
+input1.bam_1	FBtr0080664	71	71	0	F	56	0	0	1
+input1.bam_1	FBtr0080664	71	71	0	R	56	0	0	1
diff -r 000000000000 -r 6d48150495e3 test-data/doubled_mean.pdf
Binary file test-data/doubled_mean.pdf has changed
diff -r 000000000000 -r 6d48150495e3 test-data/input1.bam
Binary file test-data/input1.bam has changed
diff -r 000000000000 -r 6d48150495e3 test-data/input2.bam
Binary file test-data/input2.bam has changed
diff -r 000000000000 -r 6d48150495e3 test-data/mean.pdf
Binary file test-data/mean.pdf has changed
diff -r 000000000000 -r 6d48150495e3 test-data/median.pdf
Binary file test-data/median.pdf has changed
diff -r 000000000000 -r 6d48150495e3 test-data/output.tab
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.tab	Mon Jul 24 06:28:45 2017 -0400
@@ -0,0 +1,6144 @@
+Dataset	Chromosome	Chrom_length	Coordinate	Nbr_reads	Polarity	Max	Mean	Median	Coverage
+input1.bam	FBtr0070001	72	1	1	F	27	17.0	17.0	1
+input1.bam	FBtr0070001	72	1	0	R	27	0	0	1
+input1.bam	FBtr0070001	72	2	0	F	27	0	0	1
+input1.bam	FBtr0070001	72	2	0	R	27	0	0	1
+input1.bam	FBtr0070001	72	3	0	F	27	0	0	1
+input1.bam	FBtr0070001	72	3	0	R	27	0	0	1
+input1.bam	FBtr0070001	72	4	0	F	27	0	0	1
+input1.bam	FBtr0070001	72	4	0	R	27	0	0	1
+input1.bam	FBtr0070001	72	5	0	F	27	0	0	1
+input1.bam	FBtr0070001	72	5	0	R	27	0	0	1
+input1.bam	FBtr0070001	72	6	0	F	27	0	0	1
+input1.bam	FBtr0070001	72	6	0	R	27	0	0	1
+input1.bam	FBtr0070001	72	7	6	F	27	20.3	21.0	7
+input1.bam	FBtr0070001	72	7	0	R	27	0	0	7
+input1.bam	FBtr0070001	72	8	3	F	27	21.3	21.0	10
+input1.bam	FBtr0070001	72	8	0	R	27	0	0	10
+input1.bam	FBtr0070001	72	9	0	F	27	0	0	10
+input1.bam	FBtr0070001	72	9	0	R	27	0	0	10
+input1.bam	FBtr0070001	72	10	0	F	27	0	0	10
+input1.bam	FBtr0070001	72	10	0	R	27	0	0	10
+input1.bam	FBtr0070001	72	11	2	F	27	20.5	20.5	12
+input1.bam	FBtr0070001	72	11	0	R	27	0	0	12
+input1.bam	FBtr0070001	72	12	0	F	27	0	0	12
+input1.bam	FBtr0070001	72	12	0	R	27	0	0	12
+input1.bam	FBtr0070001	72	13	0	F	27	0	0	12
+input1.bam	FBtr0070001	72	13	0	R	27	0	0	12
+input1.bam	FBtr0070001	72	14	0	F	27	0	0	12
+input1.bam	FBtr0070001	72	14	0	R	27	0	0	12
+input1.bam	FBtr0070001	72	15	0	F	27	0	0	12
+input1.bam	FBtr0070001	72	15	0	R	27	0	0	12
+input1.bam	FBtr0070001	72	16	1	F	27	19.0	19.0	13
+input1.bam	FBtr0070001	72	16	0	R	27	0	0	13
+input1.bam	FBtr0070001	72	17	1	F	27	23.0	23.0	14
+input1.bam	FBtr0070001	72	17	0	R	27	0	0	14
+input1.bam	FBtr0070001	72	18	1	F	27	16.0	16.0	14
+input1.bam	FBtr0070001	72	18	0	R	27	0	0	14
+input1.bam	FBtr0070001	72	19	0	F	27	0	0	14
+input1.bam	FBtr0070001	72	19	0	R	27	0	0	14
+input1.bam	FBtr0070001	72	20	0	F	27	0	0	14
+input1.bam	FBtr0070001	72	20	0	R	27	0	0	14
+input1.bam	FBtr0070001	72	21	0	F	27	0	0	14
+input1.bam	FBtr0070001	72	21	0	R	27	0	0	14
+input1.bam	FBtr0070001	72	22	0	F	27	0	0	14
+input1.bam	FBtr0070001	72	22	0	R	27	0	0	14
+input1.bam	FBtr0070001	72	23	0	F	27	0	0	13
+input1.bam	FBtr0070001	72	23	0	R	27	0	0	13
+input1.bam	FBtr0070001	72	24	0	F	27	0	0	13
+input1.bam	FBtr0070001	72	24	0	R	27	0	0	13
+input1.bam	FBtr0070001	72	25	0	F	27	0	0	13
+input1.bam	FBtr0070001	72	25	0	R	27	0	0	13
+input1.bam	FBtr0070001	72	26	0	F	27	0	0	13
+input1.bam	FBtr0070001	72	26	0	R	27	0	0	13
+input1.bam	FBtr0070001	72	27	2	F	27	23.5	23.5	14
+input1.bam	FBtr0070001	72	27	0	R	27	0	0	14
+input1.bam	FBtr0070001	72	28	0	F	27	0	0	11
+input1.bam	FBtr0070001	72	28	0	R	27	0	0	11
+input1.bam	FBtr0070001	72	29	0	F	27	0	0	8
+input1.bam	FBtr0070001	72	29	0	R	27	0	0	8
+input1.bam	FBtr0070001	72	30	1	F	27	23.0	23.0	9
+input1.bam	FBtr0070001	72	30	0	R	27	0	0	9
+input1.bam	FBtr0070001	72	31	11	F	27	23.0	23.0	18
+input1.bam	FBtr0070001	72	31	0	R	27	0	0	18
+input1.bam	FBtr0070001	72	32	27	F	27	22.0	22.0	44
+input1.bam	FBtr0070001	72	32	0	R	27	0	0	44
+input1.bam	FBtr0070001	72	33	0	F	27	0	0	44
+input1.bam	FBtr0070001	72	33	0	R	27	0	0	44
+input1.bam	FBtr0070001	72	34	1	F	27	20.0	20.0	44
+input1.bam	FBtr0070001	72	34	0	R	27	0	0	44
+input1.bam	FBtr0070001	72	35	0	F	27	0	0	43
+input1.bam	FBtr0070001	72	35	0	R	27	0	0	43
+input1.bam	FBtr0070001	72	36	0	F	27	0	0	43
+input1.bam	FBtr0070001	72	36	0	R	27	0	0	43
+input1.bam	FBtr0070001	72	37	0	F	27	0	0	43
+input1.bam	FBtr0070001	72	37	0	R	27	0	0	43
+input1.bam	FBtr0070001	72	38	0	F	27	0	0	43
+input1.bam	FBtr0070001	72	38	0	R	27	0	0	43
+input1.bam	FBtr0070001	72	39	0	F	27	0	0	43
+input1.bam	FBtr0070001	72	39	0	R	27	0	0	43
+input1.bam	FBtr0070001	72	40	0	F	27	0	0	42
+input1.bam	FBtr0070001	72	40	0	R	27	0	0	42
+input1.bam	FBtr0070001	72	41	0	F	27	0	0	42
+input1.bam	FBtr0070001	72	41	0	R	27	0	0	42
+input1.bam	FBtr0070001	72	42	0	F	27	0	0	42
+input1.bam	FBtr0070001	72	42	0	R	27	0	0	42
+input1.bam	FBtr0070001	72	43	0	F	27	0	0	42
+input1.bam	FBtr0070001	72	43	0	R	27	0	0	42
+input1.bam	FBtr0070001	72	44	0	F	27	0	0	42
+input1.bam	FBtr0070001	72	44	0	R	27	0	0	42
+input1.bam	FBtr0070001	72	45	0	F	27	0	0	42
+input1.bam	FBtr0070001	72	45	0	R	27	0	0	42
+input1.bam	FBtr0070001	72	46	0	F	27	0	0	42
+input1.bam	FBtr0070001	72	46	0	R	27	0	0	42
+input1.bam	FBtr0070001	72	47	0	F	27	0	0	42
+input1.bam	FBtr0070001	72	47	0	R	27	0	0	42
+input1.bam	FBtr0070001	72	48	0	F	27	0	0	42
+input1.bam	FBtr0070001	72	48	0	R	27	0	0	42
+input1.bam	FBtr0070001	72	49	0	F	27	0	0	42
+input1.bam	FBtr0070001	72	49	0	R	27	0	0	42
+input1.bam	FBtr0070001	72	50	0	F	27	0	0	41
+input1.bam	FBtr0070001	72	50	0	R	27	0	0	41
+input1.bam	FBtr0070001	72	51	0	F	27	0	0	40
+input1.bam	FBtr0070001	72	51	0	R	27	0	0	40
+input1.bam	FBtr0070001	72	52	0	F	27	0	0	40
+input1.bam	FBtr0070001	72	52	0	R	27	0	0	40
+input1.bam	FBtr0070001	72	53	0	F	27	0	0	39
+input1.bam	FBtr0070001	72	53	0	R	27	0	0	39
+input1.bam	FBtr0070001	72	72	0	F	27	0	0	0
+input1.bam	FBtr0070533	72	1	1	F	5	15.0	15.0	1
+input1.bam	FBtr0070533	72	1	0	R	5	0	0	1
+input1.bam	FBtr0070533	72	2	0	F	5	0	0	1
+input1.bam	FBtr0070533	72	2	0	R	5	0	0	1
+input1.bam	FBtr0070533	72	3	0	F	5	0	0	1
+input1.bam	FBtr0070533	72	3	0	R	5	0	0	1
+input1.bam	FBtr0070533	72	4	0	F	5	0	0	1
+input1.bam	FBtr0070533	72	4	0	R	5	0	0	1
+input1.bam	FBtr0070533	72	5	0	F	5	0	0	1
+input1.bam	FBtr0070533	72	5	0	R	5	0	0	1
+input1.bam	FBtr0070533	72	6	0	F	5	0	0	1
+input1.bam	FBtr0070533	72	6	0	R	5	0	0	1
+input1.bam	FBtr0070533	72	7	0	F	5	0	0	1
+input1.bam	FBtr0070533	72	7	0	R	5	0	0	1
+input1.bam	FBtr0070533	72	8	0	F	5	0	0	1
+input1.bam	FBtr0070533	72	8	0	R	5	0	0	1
+input1.bam	FBtr0070533	72	9	0	F	5	0	0	1
+input1.bam	FBtr0070533	72	9	0	R	5	0	0	1
+input1.bam	FBtr0070533	72	10	0	F	5	0	0	1
+input1.bam	FBtr0070533	72	10	0	R	5	0	0	1
+input1.bam	FBtr0070533	72	11	0	F	5	0	0	1
+input1.bam	FBtr0070533	72	11	0	R	5	0	0	1
+input1.bam	FBtr0070533	72	12	2	F	5	18.0	18.0	3
+input1.bam	FBtr0070533	72	12	0	R	5	0	0	3
+input1.bam	FBtr0070533	72	13	0	F	5	0	0	3
+input1.bam	FBtr0070533	72	13	0	R	5	0	0	3
+input1.bam	FBtr0070533	72	14	0	F	5	0	0	3
+input1.bam	FBtr0070533	72	14	0	R	5	0	0	3
+input1.bam	FBtr0070533	72	15	1	F	5	15.0	15.0	4
+input1.bam	FBtr0070533	72	15	0	R	5	0	0	4
+input1.bam	FBtr0070533	72	16	0	F	5	0	0	3
+input1.bam	FBtr0070533	72	16	0	R	5	0	0	3
+input1.bam	FBtr0070533	72	17	0	F	5	0	0	3
+input1.bam	FBtr0070533	72	17	0	R	5	0	0	3
+input1.bam	FBtr0070533	72	18	0	F	5	0	0	3
+input1.bam	FBtr0070533	72	18	0	R	5	0	0	3
+input1.bam	FBtr0070533	72	19	5	F	5	21.8	22.0	8
+input1.bam	FBtr0070533	72	19	0	R	5	0	0	8
+input1.bam	FBtr0070533	72	20	1	F	5	23.0	23.0	9
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+input1.bam	FBtr0070533	72	21	1	F	5	18.0	18.0	10
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+input1.bam	FBtr0070533	72	22	1	F	5	20.0	20.0	11
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+input1.bam	FBtr0070533	72	25	1	F	5	17.0	17.0	12
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+input1.bam	FBtr0070533	72	26	1	F	5	16.0	16.0	13
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+input1.bam	FBtr0070533	72	32	4	F	5	20.5	21.0	15
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+input1.bam	FBtr0070533	72	35	0	R	5	0	0	16
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diff -r 000000000000 -r 6d48150495e3 test-data/sizes.pdf
Binary file test-data/sizes.pdf has changed
diff -r 000000000000 -r 6d48150495e3 test-data/sizes.tab
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/sizes.tab	Mon Jul 24 06:28:45 2017 -0400
@@ -0,0 +1,1045 @@
+Dataset	Chromosome	Polarity	Size	Nbr_reads
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+input2.bam	FBtr0079692	R	22	0
+input2.bam	FBtr0079693	F	15	4
+input2.bam	FBtr0079693	F	16	2
+input2.bam	FBtr0079693	F	17	0
+input2.bam	FBtr0079693	F	18	1
+input2.bam	FBtr0079693	F	19	0
+input2.bam	FBtr0079693	F	20	2
+input2.bam	FBtr0079693	R	15	0
+input2.bam	FBtr0079693	R	16	0
+input2.bam	FBtr0079693	R	17	0
+input2.bam	FBtr0079693	R	18	0
+input2.bam	FBtr0079693	R	19	0
+input2.bam	FBtr0079693	R	20	0
+input2.bam	FBtr0079694	F	15	2
+input2.bam	FBtr0079694	F	16	0
+input2.bam	FBtr0079694	F	17	1
+input2.bam	FBtr0079694	F	18	2
+input2.bam	FBtr0079694	F	19	1
+input2.bam	FBtr0079694	R	15	0
+input2.bam	FBtr0079694	R	16	0
+input2.bam	FBtr0079694	R	17	0
+input2.bam	FBtr0079694	R	18	0
+input2.bam	FBtr0079694	R	19	0
+input2.bam	FBtr0079702	F	15	2
+input2.bam	FBtr0079702	F	16	0
+input2.bam	FBtr0079702	F	17	1
+input2.bam	FBtr0079702	F	18	1
+input2.bam	FBtr0079702	R	15	0
+input2.bam	FBtr0079702	R	16	0
+input2.bam	FBtr0079702	R	17	0
+input2.bam	FBtr0079702	R	18	0
+input2.bam	FBtr0079728	F	15	3
+input2.bam	FBtr0079728	F	16	1
+input2.bam	FBtr0079728	F	17	1
+input2.bam	FBtr0079728	F	18	1
+input2.bam	FBtr0079728	R	15	0
+input2.bam	FBtr0079728	R	16	0
+input2.bam	FBtr0079728	R	17	0
+input2.bam	FBtr0079728	R	18	0
+input2.bam	FBtr0079729	F	15	1
+input2.bam	FBtr0079729	F	16	2
+input2.bam	FBtr0079729	F	17	1
+input2.bam	FBtr0079729	R	15	0
+input2.bam	FBtr0079729	R	16	0
+input2.bam	FBtr0079729	R	17	0
+input2.bam	FBtr0079752	F	17	1
+input2.bam	FBtr0079752	F	18	0
+input2.bam	FBtr0079752	F	19	0
+input2.bam	FBtr0079752	F	20	0
+input2.bam	FBtr0079752	F	21	0
+input2.bam	FBtr0079752	F	22	0
+input2.bam	FBtr0079752	F	23	0
+input2.bam	FBtr0079752	F	24	1
+input2.bam	FBtr0079752	R	17	0
+input2.bam	FBtr0079752	R	18	0
+input2.bam	FBtr0079752	R	19	0
+input2.bam	FBtr0079752	R	20	0
+input2.bam	FBtr0079752	R	21	0
+input2.bam	FBtr0079752	R	22	0
+input2.bam	FBtr0079752	R	23	0
+input2.bam	FBtr0079752	R	24	0
+input2.bam	FBtr0079820	F	15	27
+input2.bam	FBtr0079820	F	16	10
+input2.bam	FBtr0079820	F	17	7
+input2.bam	FBtr0079820	F	18	8
+input2.bam	FBtr0079820	F	19	25
+input2.bam	FBtr0079820	F	20	24
+input2.bam	FBtr0079820	F	21	7
+input2.bam	FBtr0079820	F	22	1
+input2.bam	FBtr0079820	R	15	0
+input2.bam	FBtr0079820	R	16	0
+input2.bam	FBtr0079820	R	17	0
+input2.bam	FBtr0079820	R	18	0
+input2.bam	FBtr0079820	R	19	0
+input2.bam	FBtr0079820	R	20	0
+input2.bam	FBtr0079820	R	21	0
+input2.bam	FBtr0079820	R	22	0
+input2.bam	FBtr0080609	F	17	2
+input2.bam	FBtr0080609	F	18	1
+input2.bam	FBtr0080609	F	19	2
+input2.bam	FBtr0080609	F	20	0
+input2.bam	FBtr0080609	F	21	0
+input2.bam	FBtr0080609	F	22	1
+input2.bam	FBtr0080609	F	23	1
+input2.bam	FBtr0080609	F	24	0
+input2.bam	FBtr0080609	F	25	1
+input2.bam	FBtr0080609	R	17	0
+input2.bam	FBtr0080609	R	18	0
+input2.bam	FBtr0080609	R	19	0
+input2.bam	FBtr0080609	R	20	0
+input2.bam	FBtr0080609	R	21	0
+input2.bam	FBtr0080609	R	22	0
+input2.bam	FBtr0080609	R	23	0
+input2.bam	FBtr0080609	R	24	0
+input2.bam	FBtr0080609	R	25	0
+input2.bam	FBtr0080644	F	15	8
+input2.bam	FBtr0080644	R	15	0
+input2.bam	FBtr0080646	F	15	10
+input2.bam	FBtr0080646	F	16	1
+input2.bam	FBtr0080646	F	17	0
+input2.bam	FBtr0080646	F	18	0
+input2.bam	FBtr0080646	F	19	0
+input2.bam	FBtr0080646	F	20	0
+input2.bam	FBtr0080646	F	21	1
+input2.bam	FBtr0080646	R	15	0
+input2.bam	FBtr0080646	R	16	0
+input2.bam	FBtr0080646	R	17	0
+input2.bam	FBtr0080646	R	18	0
+input2.bam	FBtr0080646	R	19	0
+input2.bam	FBtr0080646	R	20	0
+input2.bam	FBtr0080646	R	21	0
+input2.bam	FBtr0080647	F	15	9
+input2.bam	FBtr0080647	F	16	2
+input2.bam	FBtr0080647	F	17	0
+input2.bam	FBtr0080647	F	18	1
+input2.bam	FBtr0080647	R	15	0
+input2.bam	FBtr0080647	R	16	0
+input2.bam	FBtr0080647	R	17	0
+input2.bam	FBtr0080647	R	18	0
+input2.bam	FBtr0080660	F	15	11
+input2.bam	FBtr0080660	R	15	0
+input2.bam	FBtr0080663	F	15	26
+input2.bam	FBtr0080663	F	16	14
+input2.bam	FBtr0080663	F	17	14
+input2.bam	FBtr0080663	F	18	26
+input2.bam	FBtr0080663	F	19	9
+input2.bam	FBtr0080663	F	20	7
+input2.bam	FBtr0080663	F	21	4
+input2.bam	FBtr0080663	F	22	5
+input2.bam	FBtr0080663	F	23	0
+input2.bam	FBtr0080663	F	24	1
+input2.bam	FBtr0080663	R	15	0
+input2.bam	FBtr0080663	R	16	0
+input2.bam	FBtr0080663	R	17	0
+input2.bam	FBtr0080663	R	18	0
+input2.bam	FBtr0080663	R	19	0
+input2.bam	FBtr0080663	R	20	0
+input2.bam	FBtr0080663	R	21	0
+input2.bam	FBtr0080663	R	22	0
+input2.bam	FBtr0080663	R	23	0
+input2.bam	FBtr0080663	R	24	0
+input2.bam	FBtr0080664	F	15	165
+input2.bam	FBtr0080664	F	16	59
+input2.bam	FBtr0080664	F	17	20
+input2.bam	FBtr0080664	F	18	75
+input2.bam	FBtr0080664	F	19	24
+input2.bam	FBtr0080664	F	20	21
+input2.bam	FBtr0080664	F	21	8
+input2.bam	FBtr0080664	F	22	4
+input2.bam	FBtr0080664	F	23	4
+input2.bam	FBtr0080664	F	24	0
+input2.bam	FBtr0080664	F	25	3
+input2.bam	FBtr0080664	F	26	4
+input2.bam	FBtr0080664	R	15	0
+input2.bam	FBtr0080664	R	16	0
+input2.bam	FBtr0080664	R	17	0
+input2.bam	FBtr0080664	R	18	0
+input2.bam	FBtr0080664	R	19	0
+input2.bam	FBtr0080664	R	20	0
+input2.bam	FBtr0080664	R	21	0
+input2.bam	FBtr0080664	R	22	1
+input2.bam	FBtr0080664	R	23	1
+input2.bam	FBtr0080664	R	24	0
+input2.bam	FBtr0080664	R	25	0
+input2.bam	FBtr0080664	R	26	0
diff -r 000000000000 -r 6d48150495e3 test-data/test/small_rna_map.bash
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/test/small_rna_map.bash	Mon Jul 24 06:28:45 2017 -0400
@@ -0,0 +1,43 @@
+#! /bin/bash
+# Execution command : bash small_rna_map.bash <sam file>
+samtools view -h -o input.sam ../test-data/input.bam
+samfile="input.sam"
+cut -f2,3,4,5,6 ../test-data/output.tab > test-data.dat
+grep -e "^@SQ" $samfile > header.tab
+cat $samfile | perl -ne 'print unless /^@/ or ( (split /\t/)[1] != 0 and (split /\t/)[1] != 16 )' > output1.tab
+
+cat << EOF > pyscript.py
+lendic = {}
+for line in open("header.tab"):
+  fields = line[:-1].split()
+  lendic[fields[1][3:]] = fields[2][3:]
+readdic = {}
+for line in (open("output1.tab")):
+  fields = line[:-1].split()
+  key = "-".join([fields[2],fields[3],"F" if fields[1]=="0" else "R"])
+  try:
+    readdic[key] += 1
+  except KeyError:
+    readdic[key] = 1
+Out = open("output.tab", "w")
+Out.write("Chromosome\tChrom_length\tCoordinate\tNbr_reads\tPolarity\n")
+for key in sorted(readdic):
+  fields = key.split("-")
+  Chromosome, Coordinate, Polarity = fields[0], fields[1], fields[2]
+  Chrom_length = lendic[Chromosome]
+  Nbr_reads = str(readdic[key])
+  Out.write("\t".join([Chromosome, Chrom_length, Coordinate, Nbr_reads, Polarity]) )
+  Out.write("\n")
+Out.close
+EOF
+
+python ./pyscript.py
+rm output1.tab header.tab pyscript.py
+sort -k 1,1 -k 3,3n -k 5,5  output.tab -o output.tab
+if ! diff -q output.tab test-data.dat &>/dev/null; then
+  >&2 echo "different"
+else
+  >&2 echo "Test passed"
+fi
+
+rm output.tab input.sam test-data.dat