Mercurial > repos > artbio > small_rna_map
changeset 3:2e0dc6032a98 draft
planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_map commit 93f212712d9846c7aaa389de60babb332d38363e
| author | artbio |
|---|---|
| date | Tue, 18 Jul 2017 13:34:36 -0400 |
| parents | 7feee0446c5c |
| children | 6ff925458e05 |
| files | lattice_small_rna_map.r small_rna_map.py small_rna_map.r small_rna_map.xml test-data/input3.bam test-data/input4.bam test-data/output.pdf test-data/output.tab test-data/output_doubled.pdf test-data/output_doubled.tab test-data/output_lattice.pdf test-data/output_lattice_doubled.pdf |
| diffstat | 12 files changed, 1779 insertions(+), 1628 deletions(-) [+] |
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--- /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() +
--- 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)
--- 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
--- 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>
--- 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 -dataset_1 FBtr0073020 72 29 1 F 1 22.0 22.0 -dataset_1 FBtr0073125 73 1 1 F 1 29.0 29.0 -dataset_1 FBtr0073125 73 15 1 F 1 17.0 17.0 -dataset_1 FBtr0073125 73 16 1 F 1 19.0 19.0 -dataset_1 FBtr0073125 73 32 1 F 1 21.0 21.0 -dataset_1 FBtr0073857 73 1 1 F 1 19.0 19.0 -dataset_1 FBtr0073857 73 44 1 F 1 17.0 17.0 -dataset_1 FBtr0073861 73 30 1 F 1 22.0 22.0 -dataset_1 FBtr0073861 73 52 1 F 1 20.0 20.0 -dataset_1 FBtr0073865 82 1 1 F 1 25.0 25.0 -dataset_1 FBtr0073865 82 49 1 F 1 16.0 16.0 -dataset_1 FBtr0073866 82 1 1 F 1 24.0 24.0 -dataset_1 FBtr0073866 82 3 1 F 1 22.0 22.0 -dataset_1 FBtr0073872 82 1 1 F 1 18.0 18.0 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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 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--- /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 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