Mercurial > repos > nilesh > rseqc
changeset 59:dbedfc5f5a3c draft
"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/rseqc commit 247059e2527b66f1dbecf1e61496daef921040c3"
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--- a/FPKM_count.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/FPKM_count.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,6 +1,6 @@ -<tool id="rseqc_FPKM_count" name="FPKM Count" version="@WRAPPER_VERSION@.1"> +<tool id="rseqc_FPKM_count" name="FPKM Count" version="@TOOL_VERSION@.1"> <description>calculates raw read count, FPM, and FPKM for each gene</description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros> @@ -61,7 +61,7 @@ <tests> <test> <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/> - <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed"/> + <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" ftype="bed12"/> <output name="outputxls" file="output.FPKM.xls"/> </test> </tests>
--- a/RNA_fragment_size.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/RNA_fragment_size.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,8 +1,8 @@ -<tool id="rseqc_RNA_fragment_size" name="RNA fragment size" version="@WRAPPER_VERSION@.1"> +<tool id="rseqc_RNA_fragment_size" name="RNA fragment size" version="@TOOL_VERSION@.1"> <description> calculates the fragment size for each gene/transcript </description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros> @@ -34,7 +34,7 @@ <tests> <test> <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam" /> - <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" /> + <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" ftype="bed12"/> <output name="output"> <assert_contents> <has_line_matching expression="^chrom\ttx_start\ttx_end\tsymbol\tfrag_count\tfrag_mean\tfrag_median\tfrag_std$" />
--- a/RPKM_saturation.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/RPKM_saturation.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,6 +1,6 @@ -<tool id="rseqc_RPKM_saturation" name="RPKM Saturation" version="@WRAPPER_VERSION@.1"> +<tool id="rseqc_RPKM_saturation" name="RPKM Saturation" version="@TOOL_VERSION@.2"> <description>calculates raw count and RPKM values for transcript at exon, intron, and mRNA level</description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros> @@ -33,8 +33,8 @@ #end if -l ${percentileFloor} -u ${percentileCeiling} -s ${percentileStep} -c ${rpkmCutoff} - ]]> - </command> + --mapq $mapq + ]]></command> <inputs> <expand macro="bam_param" />
--- a/bam2wig.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/bam2wig.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,8 +1,8 @@ -<tool id="rseqc_bam2wig" name="BAM to Wiggle" version="@WRAPPER_VERSION@"> +<tool id="rseqc_bam2wig" name="BAM to Wiggle" version="@TOOL_VERSION@"> <description> converts all types of RNA-seq data from .bam to .wig </description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros>
--- a/bam_stat.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/bam_stat.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,8 +1,8 @@ -<tool id="rseqc_bam_stat" name="BAM/SAM Mapping Stats" version="@WRAPPER_VERSION@"> +<tool id="rseqc_bam_stat" name="BAM/SAM Mapping Stats" version="@TOOL_VERSION@"> <description> reads mapping statistics for a provided BAM or SAM file. </description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros>
--- a/clipping_profile.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/clipping_profile.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,8 +1,8 @@ -<tool id="rseqc_clipping_profile" name="Clipping Profile" version="@WRAPPER_VERSION@"> +<tool id="rseqc_clipping_profile" name="Clipping Profile" version="@TOOL_VERSION@"> <description> estimates clipping profile of RNA-seq reads from BAM or SAM file </description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros> @@ -42,7 +42,7 @@ <param name="rscript_output" value="true" /> <output name="outputpdf" file="output.clipping_profile.pdf" compare="sim_size" /> <output name="outputxls" file="output.clipping_profile.xls" /> - <output name="outputr" file="output.clipping_profile.r" /> + <output name="outputr" file="output.clipping_profile_r" /> </test> </tests>
--- a/deletion_profile.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/deletion_profile.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,8 +1,8 @@ -<tool id="rseqc_deletion_profile" name="Deletion Profile" version="@WRAPPER_VERSION@"> +<tool id="rseqc_deletion_profile" name="Deletion Profile" version="@TOOL_VERSION@"> <description> calculates the distributions of deleted nucleotides across reads </description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros> @@ -39,7 +39,7 @@ <param name="rscript_output" value="true" /> <output name="outputpdf" file="output.deletion_profile.pdf" compare="sim_size" /> <output name="outputxls" file="output.deletion_profile.txt" /> - <output name="outputr" file="output.deletion_profile.r" /> + <output name="outputr" file="output.deletion_profile_r" /> </test> </tests>
--- a/geneBody_coverage.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/geneBody_coverage.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,19 +1,13 @@ -<tool id="rseqc_geneBody_coverage" name="Gene Body Coverage (BAM)" version="@WRAPPER_VERSION@.3"> - <description> - Read coverage over gene body. - </description> - - <macros> - <import>rseqc_macros.xml</import> - </macros> - +<tool id="rseqc_geneBody_coverage" name="Gene Body Coverage (BAM)" version="@TOOL_VERSION@.3"> + <description>Read coverage over gene body</description> + <expand macro="bio_tools"/> + <macros> + <import>rseqc_macros.xml</import> + </macros> <expand macro="requirements" /> - - <expand macro="stdio" /> - - <version_command><![CDATA[geneBody_coverage.py --version]]></version_command> - - <command><![CDATA[ + <expand macro="stdio" /> + <version_command><![CDATA[geneBody_coverage.py --version]]></version_command> + <command><![CDATA[ #if str($batch_mode.batch_mode_selector) == "merge": #import re #set $input_list = [] @@ -74,7 +68,7 @@ <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" /> <param name="rscript_output" value="true" /> <output name="outputcurvespdf" file="output.geneBodyCoverage.curves.pdf" compare="sim_size" /> - <output name="outputr" file="output.geneBodyCoverage.r" /> + <output name="outputr" file="output.geneBodyCoverage_r" /> <output name="outputtxt" file="output.geneBodyCoverage.txt" /> </test> <test> @@ -82,11 +76,11 @@ <param name="batch_mode_selector" value="merge" /> <param name="inputs" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam,pairend_strandspecific_51mer_hg19_chr1_1-100000.bam,pairend_strandspecific_51mer_hg19_chr1_1-100000.bam" /> </conditional> - <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" /> + <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" ftype="bed12"/> <param name="rscript_output" value="true" /> <output name="outputcurvespdf" file="output2.geneBodyCoverage.curves.pdf" compare="sim_size" /> <output name="outputheatmappdf" file="output2.geneBodyCoverage.heatMap.pdf" compare="sim_size" /> - <output name="outputr" file="output2.geneBodyCoverage.r" /> + <output name="outputr" file="output2.geneBodyCoverage_r" /> <output name="outputtxt" file="output2.geneBodyCoverage.txt" /> </test>
--- a/geneBody_coverage2.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/geneBody_coverage2.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,8 +1,8 @@ -<tool id="rseqc_geneBody_coverage2" name="Gene Body Coverage (Bigwig)" version="@WRAPPER_VERSION@.1"> +<tool id="rseqc_geneBody_coverage2" name="Gene Body Coverage (Bigwig)" version="@TOOL_VERSION@.2"> <description> Read coverage over gene body </description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros> @@ -21,6 +21,7 @@ <inputs> <param name="input" type="data" label="Input bigwig file" format="bigwig" /> <expand macro="refgene_param" /> + <expand macro="rscript_output_param" /> </inputs> <outputs> @@ -30,12 +31,12 @@ </outputs> <tests> - <test> + <test expect_num_outputs="3"> <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bigwig" /> - <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" /> + <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" ftype="bed12"/> <param name="rscript_output" value="true" /> <output name="outputpdf" file="output.geneBodyCoverage2.curves.pdf" compare="sim_size" /> - <output name="outputr" file="output.geneBodyCoverage2.r" /> + <output name="outputr" file="output.geneBodyCoverage2_r" /> <output name="outputtxt" file="output.geneBodyCoverage2.txt" /> </test> </tests>
--- a/infer_experiment.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/infer_experiment.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,6 +1,6 @@ -<tool id="rseqc_infer_experiment" name="Infer Experiment" version="@WRAPPER_VERSION@.1"> +<tool id="rseqc_infer_experiment" name="Infer Experiment" version="@TOOL_VERSION@.1"> <description>speculates how RNA-seq were configured</description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros> @@ -33,7 +33,7 @@ <tests> <test> <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/> - <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed"/> + <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" ftype="bed12"/> <output name="output" file="output.infer_experiment.txt"/> </test> </tests>
--- a/inner_distance.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/inner_distance.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,6 +1,6 @@ -<tool id="rseqc_inner_distance" name="Inner Distance" version="@WRAPPER_VERSION@.1"> +<tool id="rseqc_inner_distance" name="Inner Distance" version="@TOOL_VERSION@.1"> <description>calculate the inner distance (or insert size) between two paired RNA reads</description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros> @@ -42,12 +42,12 @@ <tests> <test> <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/> - <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed"/> + <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" ftype="bed12"/> <param name="rscript_output" value="true" /> <output name="outputtxt" file="output.inner_distance.txt" /> <output name="outputfreqtxt" file="output.inner_distance_freq.txt" /> <output name="outputpdf" file="output.inner_distance_plot.pdf" compare="sim_size"/> - <output name="outputr" file="output.inner_distance_plot.r" /> + <output name="outputr" file="output.inner_distance_plot_r" /> </test> </tests>
--- a/insertion_profile.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/insertion_profile.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,8 +1,8 @@ -<tool id="rseqc_insertion_profile" name="Insertion Profile" version="@WRAPPER_VERSION@"> +<tool id="rseqc_insertion_profile" name="Insertion Profile" version="@TOOL_VERSION@"> <description> calculates the distribution of inserted nucleotides across reads </description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros> @@ -37,7 +37,7 @@ <param name="rscript_output" value="true" /> <output name="outputpdf" file="output.insertion_profile.pdf" compare="sim_size" /> <output name="outputxls" file="output.insertion_profile.xls" /> - <output name="outputr" file="output.insertion_profile.r" /> + <output name="outputr" file="output.insertion_profile_r" /> </test> </tests>
--- a/junction_annotation.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/junction_annotation.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,6 +1,6 @@ -<tool id="rseqc_junction_annotation" name="Junction Annotation" version="@WRAPPER_VERSION@.1"> +<tool id="rseqc_junction_annotation" name="Junction Annotation" version="@TOOL_VERSION@.1"> <description>compares detected splice junctions to reference gene model</description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros> @@ -45,10 +45,10 @@ <tests> <test> <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam" /> - <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" /> + <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" ftype="bed12"/> <param name="rscript_output" value="true" /> <output name="outputxls" file="output.junction.xls" /> - <output name="outputr" file="output.junction_plot.r" /> + <output name="outputr" file="output.junction_plot_r" /> <output name="outputpdf" file="output.splice_events.pdf" compare="sim_size" /> <output name="outputjpdf" file="output.splice_junction.pdf" compare="sim_size" /> </test>
--- a/junction_saturation.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/junction_saturation.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,6 +1,6 @@ -<tool id="rseqc_junction_saturation" name="Junction Saturation" version="@WRAPPER_VERSION@.1"> +<tool id="rseqc_junction_saturation" name="Junction Saturation" version="@TOOL_VERSION@.1"> <description>detects splice junctions from each subset and compares them to reference gene model</description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros> @@ -62,9 +62,9 @@ <tests> <test> <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam" /> - <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" /> + <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" ftype="bed12"/> <param name="rscript_output" value="true" /> - <output name="outputr" file="output.junctionSaturation_plot.r" compare="sim_size"> + <output name="outputr" file="output.junctionSaturation_plot_r" compare="sim_size"> <assert_contents> <has_line line="pdf('output.junctionSaturation_plot.pdf')" /> <has_line line="x=c(5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100)" />
--- a/mismatch_profile.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/mismatch_profile.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,8 +1,8 @@ -<tool id="rseqc_mismatch_profile" name="Mismatch Profile" version="@WRAPPER_VERSION@"> +<tool id="rseqc_mismatch_profile" name="Mismatch Profile" version="@TOOL_VERSION@"> <description> calculates the distribution of mismatches across reads </description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros> @@ -39,7 +39,7 @@ <param name="rscript_output" value="true" /> <output name="outputpdf" file="output.mismatch_profile.pdf" compare="sim_size" /> <output name="outputxls" file="output.mismatch_profile.xls"/> - <output name="outputr" file="output.mismatch_profile.r"/> + <output name="outputr" file="output.mismatch_profile_r"/> </test> </tests>
--- a/read_GC.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/read_GC.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,6 +1,6 @@ -<tool id="rseqc_read_GC" name="Read GC" version="@WRAPPER_VERSION@"> +<tool id="rseqc_read_GC" name="Read GC" version="@TOOL_VERSION@"> <description>determines GC% and read count</description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros> @@ -36,7 +36,7 @@ <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam" /> <param name="rscript_output" value="true" /> <output name="outputxls" file="output.GC.xls" /> - <output name="outputr" file="output.GC_plot.r" /> + <output name="outputr" file="output.GC_plot_r" /> <output name="outputpdf" file="output.GC_plot.pdf" compare="sim_size" /> </test> </tests>
--- a/read_NVC.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/read_NVC.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,6 +1,6 @@ -<tool id="rseqc_read_NVC" name="Read NVC" version="@WRAPPER_VERSION@"> +<tool id="rseqc_read_NVC" name="Read NVC" version="@TOOL_VERSION@"> <description>to check the nucleotide composition bias</description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros> @@ -38,7 +38,7 @@ <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam" /> <param name="rscript_output" value="true" /> <output name="outputxls" file="output.NVC.xls" /> - <output name="outputr" file="output.NVC_plot.r" /> + <output name="outputr" file="output.NVC_plot_r" /> <output name="outputpdf" file="output.NVC_plot.pdf" compare="sim_size" /> </test> </tests>
--- a/read_distribution.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/read_distribution.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,6 +1,6 @@ -<tool id="rseqc_read_distribution" name="Read Distribution" version="@WRAPPER_VERSION@.1"> +<tool id="rseqc_read_distribution" name="Read Distribution" version="@TOOL_VERSION@.1"> <description>calculates how mapped reads were distributed over genome feature</description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros> @@ -28,7 +28,7 @@ <tests> <test> <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/> - <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed"/> + <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" ftype="bed12"/> <output name="output" file="output.read_distribution.txt"/> </test> </tests>
--- a/read_duplication.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/read_duplication.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,6 +1,6 @@ -<tool id="rseqc_read_duplication" name="Read Duplication" version="@WRAPPER_VERSION@"> +<tool id="rseqc_read_duplication" name="Read Duplication" version="@TOOL_VERSION@"> <description>determines reads duplication rate with sequence-based and mapping-based strategies</description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros> @@ -36,7 +36,7 @@ <param name="rscript_output" value="true" /> <output name="outputxls" file="output.pos.DupRate.xls" /> <output name="outputseqxls" file="output.seq.DupRate.xls" /> - <output name="outputr" file="output.DupRate_plot.r" /> + <output name="outputr" file="output.DupRate_plot_r" /> <output name="outputpdf" file="output.DupRate_plot.pdf" compare="sim_size" /> </test> </tests>
--- a/read_hexamer.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/read_hexamer.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,8 +1,8 @@ -<tool id="rseqc_read_hexamer" name="Hexamer frequency" version="@WRAPPER_VERSION@"> +<tool id="rseqc_read_hexamer" name="Hexamer frequency" version="@TOOL_VERSION@"> <description> calculates hexamer (6mer) frequency for reads, genomes, and mRNA sequences </description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros>
--- a/read_quality.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/read_quality.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,6 +1,6 @@ -<tool id="rseqc_read_quality" name="Read Quality" version="@WRAPPER_VERSION@"> +<tool id="rseqc_read_quality" name="Read Quality" version="@TOOL_VERSION@"> <description>determines Phred quality score</description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros> @@ -43,7 +43,7 @@ <test> <param name="input" value="pairend_strandspecific_51mer_hg19_random.bam"/> <param name="rscript_output" value="true" /> - <output name="outputr" file="output.qual.r"/> + <output name="outputr" file="output.qual_r"/> <output name="outputheatpdf" file="output.qual.heatmap.pdf" compare="sim_size" /> <output name="outputboxpdf" file="output.qual.boxplot.pdf" compare="sim_size" /> </test>
--- a/rseqc_macros.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/rseqc_macros.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,6 +1,6 @@ <macros> - <token name="@WRAPPER_VERSION@">2.6.4</token> + <token name="@TOOL_VERSION@">2.6.4</token> <xml name="requirements"> <requirements> @@ -8,7 +8,11 @@ <yield/> </requirements> </xml> - + <xml name="bio_tools"> + <xrefs> + <xref type="bio.tools">rseqc</xref> + </xrefs> + </xml> <xml name="stdio"> <stdio> <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
--- a/test-data/output.DupRate_plot.r Thu Nov 28 15:56:37 2019 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,14 +0,0 @@ -pdf('output.DupRate_plot.pdf') -par(mar=c(5,4,4,5),las=0) -seq_occ=c(1) -seq_uniqRead=c(40) -pos_occ=c(1) -pos_uniqRead=c(40) -plot(pos_occ,log10(pos_uniqRead),ylab='Number of Reads (log10)',xlab='Occurrence of read',pch=4,cex=0.8,col='blue',xlim=c(1,500),yaxt='n') -points(seq_occ,log10(seq_uniqRead),pch=20,cex=0.8,col='red') -ym=floor(max(log10(pos_uniqRead))) -legend(300,ym,legend=c('Sequence-based','Mapping-based'),col=c('blue','red'),pch=c(4,20)) -axis(side=2,at=0:ym,labels=0:ym) -axis(side=4,at=c(log10(pos_uniqRead[1]),log10(pos_uniqRead[2]),log10(pos_uniqRead[3]),log10(pos_uniqRead[4])), labels=c(round(pos_uniqRead[1]*100/sum(pos_uniqRead*pos_occ)),round(pos_uniqRead[2]*100/sum(pos_uniqRead*pos_occ)),round(pos_uniqRead[3]*100/sum(pos_uniqRead*pos_occ)),round(pos_uniqRead[4]*100/sum(pos_uniqRead*pos_occ)))) -mtext(4, text = "Reads %", line = 2) -dev.off()
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/output.DupRate_plot_r Sat Dec 18 19:41:19 2021 +0000 @@ -0,0 +1,14 @@ +pdf('output.DupRate_plot.pdf') +par(mar=c(5,4,4,5),las=0) +seq_occ=c(1) +seq_uniqRead=c(40) +pos_occ=c(1) +pos_uniqRead=c(40) +plot(pos_occ,log10(pos_uniqRead),ylab='Number of Reads (log10)',xlab='Occurrence of read',pch=4,cex=0.8,col='blue',xlim=c(1,500),yaxt='n') +points(seq_occ,log10(seq_uniqRead),pch=20,cex=0.8,col='red') +ym=floor(max(log10(pos_uniqRead))) +legend(300,ym,legend=c('Sequence-based','Mapping-based'),col=c('blue','red'),pch=c(4,20)) +axis(side=2,at=0:ym,labels=0:ym) +axis(side=4,at=c(log10(pos_uniqRead[1]),log10(pos_uniqRead[2]),log10(pos_uniqRead[3]),log10(pos_uniqRead[4])), labels=c(round(pos_uniqRead[1]*100/sum(pos_uniqRead*pos_occ)),round(pos_uniqRead[2]*100/sum(pos_uniqRead*pos_occ)),round(pos_uniqRead[3]*100/sum(pos_uniqRead*pos_occ)),round(pos_uniqRead[4]*100/sum(pos_uniqRead*pos_occ)))) +mtext(4, text = "Reads %", line = 2) +dev.off()
--- a/test-data/output.GC_plot.r Thu Nov 28 15:56:37 2019 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,4 +0,0 @@ -pdf("output.GC_plot.pdf") -gc=rep(c(60.78,41.18,47.06,56.86,29.41,27.45,37.25,78.43,58.82,50.98,49.02,62.75,68.63,54.90,52.94,35.29,43.14,39.22),times=c(3,3,5,7,1,2,2,1,1,3,2,1,1,1,3,1,2,1)) -hist(gc,probability=T,breaks=100,xlab="GC content (%)",ylab="Density of Reads",border="blue",main="") -dev.off()
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/output.GC_plot_r Sat Dec 18 19:41:19 2021 +0000 @@ -0,0 +1,4 @@ +pdf("output.GC_plot.pdf") +gc=rep(c(60.78,41.18,47.06,56.86,29.41,27.45,37.25,78.43,58.82,50.98,49.02,62.75,68.63,54.90,52.94,35.29,43.14,39.22),times=c(3,3,5,7,1,2,2,1,1,3,2,1,1,1,3,1,2,1)) +hist(gc,probability=T,breaks=100,xlab="GC content (%)",ylab="Density of Reads",border="blue",main="") +dev.off()
--- a/test-data/output.NVC_plot.r Thu Nov 28 15:56:37 2019 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,17 +0,0 @@ -position=c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50) -A_count=c(5,6,5,11,5,4,11,9,12,8,9,9,14,10,9,10,8,9,7,12,10,9,14,13,12,9,11,11,13,9,8,7,7,11,6,8,9,11,8,8,12,9,10,7,10,10,7,9,10,8,7) -C_count=c(7,7,9,9,9,11,7,8,9,9,8,6,8,6,9,10,4,9,5,8,6,9,6,11,8,13,16,8,6,9,6,9,8,11,12,17,8,9,9,12,9,13,12,13,12,10,10,9,6,10,8) -G_count=c(18,15,18,14,12,19,12,12,11,8,9,11,12,9,7,9,6,10,11,4,9,15,11,11,7,4,7,13,9,12,15,11,14,10,13,11,7,12,10,11,10,11,9,11,6,9,10,12,14,13,9) -T_count=c(10,8,5,4,14,6,10,9,8,10,14,14,6,15,15,9,14,9,12,10,15,7,9,5,10,8,6,8,12,10,11,13,11,8,9,4,16,8,13,9,9,7,9,9,12,11,13,10,10,9,16) -N_count=c(0,4,3,2,0,0,0,2,0,5,0,0,0,0,0,2,8,3,5,6,0,0,0,0,3,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0) -X_count=c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0) -total= A_count + C_count + G_count + T_count -ym=max(A_count/total,C_count/total,G_count/total,T_count/total) + 0.05 -yn=min(A_count/total,C_count/total,G_count/total,T_count/total) -pdf("output.NVC_plot.pdf") -plot(position,A_count/total,type="o",pch=20,ylim=c(yn,ym),col="dark green",xlab="Position of Read",ylab="Nucleotide Frequency") -lines(position,T_count/total,type="o",pch=20,col="red") -lines(position,G_count/total,type="o",pch=20,col="blue") -lines(position,C_count/total,type="o",pch=20,col="cyan") -legend(41,ym,legend=c("A","T","G","C"),col=c("dark green","red","blue","cyan"),lwd=2,pch=20,text.col=c("dark green","red","blue","cyan")) -dev.off()
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/output.NVC_plot_r Sat Dec 18 19:41:19 2021 +0000 @@ -0,0 +1,17 @@ +position=c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50) +A_count=c(5,6,5,11,5,4,11,9,12,8,9,9,14,10,9,10,8,9,7,12,10,9,14,13,12,9,11,11,13,9,8,7,7,11,6,8,9,11,8,8,12,9,10,7,10,10,7,9,10,8,7) +C_count=c(7,7,9,9,9,11,7,8,9,9,8,6,8,6,9,10,4,9,5,8,6,9,6,11,8,13,16,8,6,9,6,9,8,11,12,17,8,9,9,12,9,13,12,13,12,10,10,9,6,10,8) +G_count=c(18,15,18,14,12,19,12,12,11,8,9,11,12,9,7,9,6,10,11,4,9,15,11,11,7,4,7,13,9,12,15,11,14,10,13,11,7,12,10,11,10,11,9,11,6,9,10,12,14,13,9) +T_count=c(10,8,5,4,14,6,10,9,8,10,14,14,6,15,15,9,14,9,12,10,15,7,9,5,10,8,6,8,12,10,11,13,11,8,9,4,16,8,13,9,9,7,9,9,12,11,13,10,10,9,16) +N_count=c(0,4,3,2,0,0,0,2,0,5,0,0,0,0,0,2,8,3,5,6,0,0,0,0,3,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0) +X_count=c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0) +total= A_count + C_count + G_count + T_count +ym=max(A_count/total,C_count/total,G_count/total,T_count/total) + 0.05 +yn=min(A_count/total,C_count/total,G_count/total,T_count/total) +pdf("output.NVC_plot.pdf") +plot(position,A_count/total,type="o",pch=20,ylim=c(yn,ym),col="dark green",xlab="Position of Read",ylab="Nucleotide Frequency") +lines(position,T_count/total,type="o",pch=20,col="red") +lines(position,G_count/total,type="o",pch=20,col="blue") +lines(position,C_count/total,type="o",pch=20,col="cyan") +legend(41,ym,legend=c("A","T","G","C"),col=c("dark green","red","blue","cyan"),lwd=2,pch=20,text.col=c("dark green","red","blue","cyan")) +dev.off()
--- a/test-data/output.clipping_profile.r Thu Nov 28 15:56:37 2019 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,6 +0,0 @@ -pdf("output.clipping_profile.pdf") -read_pos=c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50) -clip_count=c(16.0,12.0,11.0,8.0,7.0,6.0,1.0,1.0,1.0,1.0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1.0,1.0,1.0,2.0,3.0,4.0,4.0) -nonclip_count= 40 - clip_count -plot(read_pos, nonclip_count*100/(clip_count+nonclip_count),col="blue",main="clipping profile",xlab="Position of read",ylab="Non-clipped %",type="b") -dev.off()
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/output.clipping_profile_r Sat Dec 18 19:41:19 2021 +0000 @@ -0,0 +1,6 @@ +pdf("output.clipping_profile.pdf") +read_pos=c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50) +clip_count=c(16.0,12.0,11.0,8.0,7.0,6.0,1.0,1.0,1.0,1.0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1.0,1.0,1.0,2.0,3.0,4.0,4.0) +nonclip_count= 40 - clip_count +plot(read_pos, nonclip_count*100/(clip_count+nonclip_count),col="blue",main="clipping profile",xlab="Position of read",ylab="Non-clipped %",type="b") +dev.off()
--- a/test-data/output.deletion_profile.r Thu Nov 28 15:56:37 2019 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,5 +0,0 @@ -pdf("output.deletion_profile.pdf") -pos=c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100) -value=c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0) -plot(pos,value,type='b', col='blue',xlab="Read position (5'->3')", ylab='Deletion count') -dev.off()
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/output.deletion_profile_r Sat Dec 18 19:41:19 2021 +0000 @@ -0,0 +1,5 @@ +pdf("output.deletion_profile.pdf") +pos=c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100) +value=c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0) +plot(pos,value,type='b', col='blue',xlab="Read position (5'->3')", ylab='Deletion count') +dev.off()
--- a/test-data/output.geneBodyCoverage.r Thu Nov 28 15:56:37 2019 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,8 +0,0 @@ -pairend_strandspecific_51mer_hg19_chr1_1_100000_bam <- c(0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0) - - -pdf("output.geneBodyCoverage.curves.pdf") -x=1:100 -icolor = colorRampPalette(c("#7fc97f","#beaed4","#fdc086","#ffff99","#386cb0","#f0027f"))(1) -plot(x,pairend_strandspecific_51mer_hg19_chr1_1_100000_bam,type='l',xlab="Gene body percentile (5'->3')", ylab="Coverage",lwd=0.8,col=icolor[1]) -dev.off()
--- a/test-data/output.geneBodyCoverage2.r Thu Nov 28 15:56:37 2019 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,5 +0,0 @@ -pdf('output.geneBodyCoverage.pdf') -x=1:100 -y=c(0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0) -plot(x,y/7,xlab="percentile of gene body (5'->3')",ylab='average wigsum',type='s') -dev.off()
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/output.geneBodyCoverage2_r Sat Dec 18 19:41:19 2021 +0000 @@ -0,0 +1,5 @@ +pdf('output.geneBodyCoverage.pdf') +x=1:100 +y=c(0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0) +plot(x,y/7,xlab="percentile of gene body (5'->3')",ylab='average wigsum',type='s') +dev.off()
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/output.geneBodyCoverage_r Sat Dec 18 19:41:19 2021 +0000 @@ -0,0 +1,8 @@ +pairend_strandspecific_51mer_hg19_chr1_1_100000_bam <- c(0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0) + + +pdf("output.geneBodyCoverage.curves.pdf") +x=1:100 +icolor = colorRampPalette(c("#7fc97f","#beaed4","#fdc086","#ffff99","#386cb0","#f0027f"))(1) +plot(x,pairend_strandspecific_51mer_hg19_chr1_1_100000_bam,type='l',xlab="Gene body percentile (5'->3')", ylab="Coverage",lwd=0.8,col=icolor[1]) +dev.off()
--- a/test-data/output.inner_distance_plot.r Thu Nov 28 15:56:37 2019 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,11 +0,0 @@ -out_file = 'output' -pdf('output.inner_distance_plot.pdf') -fragsize=rep(c(-248,-243,-238,-233,-228,-223,-218,-213,-208,-203,-198,-193,-188,-183,-178,-173,-168,-163,-158,-153,-148,-143,-138,-133,-128,-123,-118,-113,-108,-103,-98,-93,-88,-83,-78,-73,-68,-63,-58,-53,-48,-43,-38,-33,-28,-23,-18,-13,-8,-3,2,7,12,17,22,27,32,37,42,47,52,57,62,67,72,77,82,87,92,97,102,107,112,117,122,127,132,137,142,147,152,157,162,167,172,177,182,187,192,197,202,207,212,217,222,227,232,237,242,247),times=c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,1,0,0,2,0,0,2,0,0,0,1,0,1,1,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,1,0,1,0,0,0,0,0,0,0,1,0,1,1,0,1,0,1,0,0,0)) -frag_sd = sd(fragsize) -frag_mean = mean(fragsize) -frag_median = median(fragsize) -write(x=c("Name","Mean","Median","sd"), sep=" ", file=stdout(),ncolumns=4) -write(c(out_file,frag_mean,frag_median,frag_sd),sep=" ", file=stdout(),ncolumns=4) -hist(fragsize,probability=T,breaks=100,xlab="mRNA insert size (bp)",main=paste(c("Mean=",frag_mean,";","SD=",frag_sd),collapse=""),border="blue") -lines(density(fragsize,bw=10),col='red') -dev.off()
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/output.inner_distance_plot_r Sat Dec 18 19:41:19 2021 +0000 @@ -0,0 +1,11 @@ +out_file = 'output' +pdf('output.inner_distance_plot.pdf') +fragsize=rep(c(-248,-243,-238,-233,-228,-223,-218,-213,-208,-203,-198,-193,-188,-183,-178,-173,-168,-163,-158,-153,-148,-143,-138,-133,-128,-123,-118,-113,-108,-103,-98,-93,-88,-83,-78,-73,-68,-63,-58,-53,-48,-43,-38,-33,-28,-23,-18,-13,-8,-3,2,7,12,17,22,27,32,37,42,47,52,57,62,67,72,77,82,87,92,97,102,107,112,117,122,127,132,137,142,147,152,157,162,167,172,177,182,187,192,197,202,207,212,217,222,227,232,237,242,247),times=c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,1,0,0,2,0,0,2,0,0,0,1,0,1,1,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,1,0,1,0,0,0,0,0,0,0,1,0,1,1,0,1,0,1,0,0,0)) +frag_sd = sd(fragsize) +frag_mean = mean(fragsize) +frag_median = median(fragsize) +write(x=c("Name","Mean","Median","sd"), sep=" ", file=stdout(),ncolumns=4) +write(c(out_file,frag_mean,frag_median,frag_sd),sep=" ", file=stdout(),ncolumns=4) +hist(fragsize,probability=T,breaks=100,xlab="mRNA insert size (bp)",main=paste(c("Mean=",frag_mean,";","SD=",frag_sd),collapse=""),border="blue") +lines(density(fragsize,bw=10),col='red') +dev.off()
--- a/test-data/output.insertion_profile.r Thu Nov 28 15:56:37 2019 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,6 +0,0 @@ -pdf("output.insertion_profile.pdf") -read_pos=c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50) -insert_count=c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0) -noninsert_count= 40 - insert_count -plot(read_pos, insert_count*100/(insert_count+noninsert_count),col="blue",main="Insertion profile",xlab="Position of read",ylab="Insertion %",type="b") -dev.off()
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/output.insertion_profile_r Sat Dec 18 19:41:19 2021 +0000 @@ -0,0 +1,6 @@ +pdf("output.insertion_profile.pdf") +read_pos=c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50) +insert_count=c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0) +noninsert_count= 40 - insert_count +plot(read_pos, insert_count*100/(insert_count+noninsert_count),col="blue",main="Insertion profile",xlab="Position of read",ylab="Insertion %",type="b") +dev.off()
--- a/test-data/output.junctionSaturation_plot.r Thu Nov 28 15:56:37 2019 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,12 +0,0 @@ -pdf('output.junctionSaturation_plot.pdf') -x=c(5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100) -y=c(0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1) -z=c(0,0,0,0,0,0,1,1,1,1,1,1,1,2,2,2,2,2,2,3) -w=c(0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,2) -m=max(0,0,0) -n=min(0,0,0) -plot(x,z/1000,xlab='percent of total reads',ylab='Number of splicing junctions (x1000)',type='o',col='blue',ylim=c(n,m)) -points(x,y/1000,type='o',col='red') -points(x,w/1000,type='o',col='green') -legend(5,0, legend=c("All junctions","known junctions", "novel junctions"),col=c("blue","red","green"),lwd=1,pch=1) -dev.off()
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/output.junctionSaturation_plot_r Sat Dec 18 19:41:19 2021 +0000 @@ -0,0 +1,12 @@ +pdf('output.junctionSaturation_plot.pdf') +x=c(5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100) +y=c(0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1) +z=c(0,0,0,0,0,0,1,1,1,1,1,1,1,2,2,2,2,2,2,3) +w=c(0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,2) +m=max(0,0,0) +n=min(0,0,0) +plot(x,z/1000,xlab='percent of total reads',ylab='Number of splicing junctions (x1000)',type='o',col='blue',ylim=c(n,m)) +points(x,y/1000,type='o',col='red') +points(x,w/1000,type='o',col='green') +legend(5,0, legend=c("All junctions","known junctions", "novel junctions"),col=c("blue","red","green"),lwd=1,pch=1) +dev.off()
--- a/test-data/output.junction_plot.r Thu Nov 28 15:56:37 2019 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,8 +0,0 @@ -pdf("output.splice_events.pdf") -events=c(25.0,25.0,25.0) -pie(events,col=c(2,3,4),init.angle=30,angle=c(60,120,150),density=c(70,70,70),main="splicing events",labels=c("partial_novel 25%","complete_novel 25%","known 25%")) -dev.off() -pdf("output.splice_junction.pdf") -junction=c(33.3333333333,33.3333333333,33.3333333333) -pie(junction,col=c(2,3,4),init.angle=30,angle=c(60,120,150),density=c(70,70,70),main="splicing junctions",labels=c("partial_novel 33%","complete_novel 33%","known 33%")) -dev.off()
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/output.junction_plot_r Sat Dec 18 19:41:19 2021 +0000 @@ -0,0 +1,8 @@ +pdf("output.splice_events.pdf") +events=c(25.0,25.0,25.0) +pie(events,col=c(2,3,4),init.angle=30,angle=c(60,120,150),density=c(70,70,70),main="splicing events",labels=c("partial_novel 25%","complete_novel 25%","known 25%")) +dev.off() +pdf("output.splice_junction.pdf") +junction=c(33.3333333333,33.3333333333,33.3333333333) +pie(junction,col=c(2,3,4),init.angle=30,angle=c(60,120,150),density=c(70,70,70),main="splicing junctions",labels=c("partial_novel 33%","complete_novel 33%","known 33%")) +dev.off()
--- a/test-data/output.qual.r Thu Nov 28 15:56:37 2019 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,62 +0,0 @@ -pdf('output.qual.boxplot.pdf') -p0<-rep(c(33,37,38,39,40,41,42,43,44,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(119,2,3,2,5,6,8,6,2,3,11,16,6,26,11,13,25,39,7,40,33,33,58,51,116,87,55,256,54,323,263,140,812,654,1119)/1000) -p1<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(105,2,2,2,4,8,6,21,3,1,1,8,13,13,16,16,14,29,32,18,50,30,57,66,73,97,105,60,253,57,330,270,142,801,630,1069)/1000) -p2<-rep(c(33,35,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(109,1,1,3,2,7,11,14,13,2,4,3,8,14,21,27,17,14,26,39,11,37,28,74,64,55,86,106,62,234,56,326,269,147,787,645,1081)/1000) -p3<-rep(c(33,37,38,39,40,41,42,43,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(108,1,6,4,2,9,12,7,3,3,9,14,13,24,20,8,24,46,14,43,28,59,67,75,88,107,51,285,56,293,239,139,802,660,1084)/1000) -p4<-rep(c(33,35,37,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(97,1,1,3,9,8,11,5,4,2,4,10,16,19,24,7,8,35,43,19,49,29,51,67,51,93,107,43,306,65,345,223,123,789,661,1075)/1000) -p5<-rep(c(33,37,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(96,3,2,5,11,6,8,2,7,2,12,17,15,16,12,11,25,31,12,32,36,59,70,69,74,99,56,277,59,343,249,111,845,650,1081)/1000) -p6<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(86,2,4,2,6,12,8,10,1,7,7,9,11,14,26,14,9,14,53,17,34,41,55,71,76,76,117,62,238,62,339,229,155,798,607,1131)/1000) -p7<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(76,1,4,4,6,11,9,13,5,5,6,6,17,19,20,17,8,19,45,15,30,33,60,68,58,76,99,59,291,54,349,251,129,818,602,1120)/1000) -p8<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(74,1,2,3,1,5,6,6,7,7,2,4,11,11,16,24,13,9,24,48,19,33,39,63,67,68,78,104,66,284,62,329,240,147,749,649,1132)/1000) -p9<-rep(c(33,37,38,39,40,41,42,43,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(98,1,2,2,6,11,19,10,5,3,8,18,19,24,14,5,18,53,21,41,39,56,79,64,70,93,57,291,42,334,259,143,795,616,1087)/1000) -p10<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(71,3,3,4,3,5,6,7,2,3,5,13,14,6,17,21,12,27,40,16,34,39,46,64,78,103,103,63,279,37,314,239,118,805,674,1129)/1000) -p11<-rep(c(33,34,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(76,1,4,3,3,7,10,11,8,5,6,3,12,13,18,21,16,18,21,46,21,32,41,77,56,77,103,105,54,269,40,320,247,144,796,621,1098)/1000) -p12<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(87,3,2,1,7,12,8,6,5,13,8,11,9,16,23,13,14,22,40,21,53,48,51,59,77,84,126,75,282,48,306,254,151,808,586,1074)/1000) -p13<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(76,5,1,3,6,3,7,8,4,3,10,12,14,13,23,12,19,25,43,17,52,42,63,57,92,91,114,61,281,45,342,256,132,812,586,1073)/1000) -p14<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(81,1,5,4,4,10,11,9,3,5,5,6,18,21,29,26,14,27,51,17,54,47,51,65,84,84,118,66,291,46,316,244,149,782,579,1080)/1000) -p15<-rep(c(33,36,37,38,39,40,41,42,43,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(87,1,2,5,2,10,17,12,9,7,2,10,10,12,20,18,21,27,50,17,50,54,42,82,57,84,103,54,285,41,342,265,115,822,582,1085)/1000) -p16<-rep(c(33,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(118,4,3,7,7,11,10,5,6,8,11,18,19,30,34,13,34,47,14,62,49,55,83,82,96,101,51,283,45,346,249,152,843,521,985)/1000) -p17<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(73,2,5,6,7,9,11,7,5,4,11,19,13,15,33,18,17,42,57,25,46,65,67,94,68,93,117,67,279,53,306,295,132,844,504,993)/1000) -p18<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(72,1,2,3,5,4,16,13,14,2,8,2,18,19,27,37,27,18,29,57,21,47,57,62,87,81,89,111,57,293,49,319,270,142,858,495,990)/1000) -p19<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(78,1,1,5,3,3,13,10,13,5,7,5,14,15,24,30,23,23,24,57,19,72,49,70,70,72,91,124,60,298,52,347,270,147,841,486,980)/1000) -p20<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(71,4,5,3,10,9,10,12,5,9,6,23,14,19,33,27,21,34,60,16,47,57,55,82,84,109,117,44,305,45,335,265,146,856,510,954)/1000) -p21<-rep(c(33,37,38,39,40,41,42,43,44,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(80,5,4,5,4,6,10,7,4,11,14,19,18,32,25,29,32,75,19,58,56,66,81,79,102,133,52,332,44,306,260,152,879,486,917)/1000) -p22<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(80,2,5,2,11,11,13,4,4,5,8,12,15,21,34,27,18,44,58,26,72,62,72,90,84,97,137,51,324,54,332,254,143,857,492,881)/1000) -p23<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(78,3,4,1,9,9,3,8,9,9,5,12,20,19,37,30,23,38,69,29,64,51,71,95,92,99,133,52,320,51,340,275,152,868,467,856)/1000) -p24<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(73,1,2,3,6,14,19,7,3,3,10,24,15,26,38,27,15,34,71,17,62,72,75,86,84,108,128,65,304,41,356,239,139,864,494,876)/1000) -p25<-rep(c(33,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(100,1,1,6,3,6,14,19,11,9,7,11,5,8,25,21,35,16,18,39,61,19,65,42,62,91,83,80,105,38,318,50,372,289,135,847,504,884)/1000) -p26<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(72,1,1,4,2,12,10,17,11,5,3,3,21,25,29,34,34,19,38,55,20,55,59,82,96,99,106,133,45,299,71,339,265,157,822,474,882)/1000) -p27<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(73,1,2,5,3,17,16,6,5,7,11,7,16,14,30,31,16,45,71,29,50,62,72,78,77,107,132,62,273,47,366,277,161,892,462,877)/1000) -p28<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(91,3,2,2,7,10,6,9,9,6,11,15,17,19,33,20,10,30,54,20,68,48,73,84,72,114,131,60,321,60,356,270,159,874,496,840)/1000) -p29<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(92,1,5,5,4,6,8,7,10,4,7,7,16,26,24,33,20,22,36,49,15,53,65,71,79,80,112,127,63,320,49,359,292,141,837,455,900)/1000) -p30<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(105,1,2,5,4,2,15,8,13,8,6,7,19,24,21,30,22,17,35,53,13,52,61,45,93,74,87,120,60,302,41,331,272,131,877,513,931)/1000) -p31<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(117,3,5,3,11,23,24,10,5,7,6,8,13,12,40,18,18,40,41,12,45,57,72,86,71,75,125,68,299,55,302,264,154,874,464,973)/1000) -p32<-rep(c(33,35,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(120,1,7,3,4,9,13,19,8,5,3,10,17,25,13,19,18,23,33,49,25,41,51,72,74,56,95,112,60,291,58,281,267,145,916,463,993)/1000) -p33<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(89,1,4,9,13,7,8,7,8,6,8,8,18,20,12,34,26,14,31,50,17,45,65,58,68,77,84,110,66,289,54,284,282,164,871,489,1003)/1000) -p34<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(162,1,3,4,4,14,15,24,17,2,6,9,16,15,20,37,20,12,34,49,12,42,50,54,66,62,81,121,56,265,50,292,258,127,878,506,1015)/1000) -p35<-rep(c(33,37,38,39,40,41,42,43,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(79,5,1,3,3,13,8,6,7,11,15,19,11,17,25,16,34,49,16,37,45,69,72,76,79,101,48,303,38,326,254,140,811,619,1043)/1000) -p36<-rep(c(33,37,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(78,3,4,3,8,5,6,8,6,5,13,18,18,32,19,22,39,43,17,39,45,68,77,74,69,118,47,272,47,332,262,139,833,562,1068)/1000) -p37<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(96,1,3,1,5,5,6,6,8,4,7,3,12,9,18,35,15,24,27,57,20,40,53,70,81,89,91,117,46,262,44,298,251,130,817,588,1059)/1000) -p38<-rep(c(33,37,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(102,5,5,4,10,11,12,3,3,7,8,18,15,22,20,17,20,50,21,46,43,71,70,80,91,110,51,239,34,339,258,119,820,614,1058)/1000) -p39<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(100,3,5,3,6,10,12,12,5,5,10,6,21,18,28,14,16,33,38,18,45,56,58,71,65,79,109,57,253,47,310,263,129,854,616,1017)/1000) -p40<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(97,1,4,3,1,5,14,7,11,2,5,2,9,6,19,21,18,21,30,37,22,37,64,40,69,53,89,104,66,281,42,355,233,137,771,615,1095)/1000) -p41<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(130,5,2,6,10,10,19,20,5,5,4,12,16,17,28,14,12,25,42,16,42,39,57,61,73,84,110,49,261,48,315,254,125,761,643,1028)/1000) -p42<-rep(c(33,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(108,2,1,2,1,5,4,12,13,7,6,7,3,6,14,19,20,22,15,22,52,14,50,45,57,67,72,78,119,51,272,45,284,226,127,831,604,1054)/1000) -p43<-rep(c(33,35,36,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(124,2,2,1,2,5,13,17,10,1,6,4,14,11,19,31,14,14,24,30,12,42,41,54,64,74,82,112,68,250,49,308,261,142,775,557,1060)/1000) -p44<-rep(c(33,35,37,38,39,40,41,42,43,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(106,1,1,4,4,10,9,9,7,9,6,8,8,16,21,12,18,24,50,14,43,43,56,55,100,87,109,51,261,51,308,217,139,759,562,1041)/1000) -p45<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(120,3,3,2,9,7,12,9,6,4,1,10,9,15,26,11,16,22,35,16,26,45,50,60,56,67,74,62,247,50,282,243,123,747,618,1061)/1000) -p46<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(116,1,2,3,2,10,15,10,1,2,6,6,10,9,13,8,14,29,26,12,31,42,59,41,57,88,92,58,257,43,304,236,133,707,612,1016)/1000) -p47<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(130,1,2,4,2,6,8,18,21,3,5,5,7,12,15,17,7,7,23,43,9,28,32,44,42,56,68,83,54,225,38,289,181,133,713,594,991)/1000) -p48<-rep(c(33,35,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(105,1,5,2,6,9,10,23,1,5,3,3,9,9,30,13,7,18,27,12,28,24,49,42,63,75,81,45,226,43,274,217,147,676,571,925)/1000) -p49<-rep(c(33,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(99,3,1,3,5,5,16,3,3,6,7,4,13,15,11,3,10,34,16,20,37,46,41,52,66,85,35,201,45,253,201,119,685,497,913)/1000) -p50<-rep(c(33,43,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(82,2,3,5,3,4,5,13,9,5,11,14,3,35,17,21,41,34,67,67,31,184,49,241,167,93,639,515,797)/1000) -boxplot(p0,p1,p2,p3,p4,p5,p6,p7,p8,p9,p10,p11,p12,p13,p14,p15,p16,p17,p18,p19,p20,p21,p22,p23,p24,p25,p26,p27,p28,p29,p30,p31,p32,p33,p34,p35,p36,p37,p38,p39,p40,p41,p42,p43,p44,p45,p46,p47,p48,p49,p50,xlab="Position of Read(5'->3')",ylab="Phred Quality Score",outline=F) -dev.off() - - -pdf('output.qual.heatmap.pdf') -qual=c(119,0,0,0,2,3,2,5,6,8,6,2,0,3,11,16,6,26,11,13,25,39,7,40,33,33,58,51,116,87,55,256,54,323,263,140,812,654,1119,105,0,0,0,2,2,2,4,8,6,21,3,1,1,8,13,13,16,16,14,29,32,18,50,30,57,66,73,97,105,60,253,57,330,270,142,801,630,1069,109,0,1,0,1,3,2,7,11,14,13,2,4,3,8,14,21,27,17,14,26,39,11,37,28,74,64,55,86,106,62,234,56,326,269,147,787,645,1081,108,0,0,0,1,6,4,2,9,12,7,0,3,3,9,14,13,24,20,8,24,46,14,43,28,59,67,75,88,107,51,285,56,293,239,139,802,660,1084,97,0,1,0,1,0,3,9,8,11,5,4,2,4,10,16,19,24,7,8,35,43,19,49,29,51,67,51,93,107,43,306,65,345,223,123,789,661,1075,96,0,0,0,3,0,2,5,11,6,8,2,7,2,12,17,15,16,12,11,25,31,12,32,36,59,70,69,74,99,56,277,59,343,249,111,845,650,1081,86,0,0,0,2,4,2,6,12,8,10,1,7,7,9,11,14,26,14,9,14,53,17,34,41,55,71,76,76,117,62,238,62,339,229,155,798,607,1131,76,0,0,0,1,4,4,6,11,9,13,5,5,6,6,17,19,20,17,8,19,45,15,30,33,60,68,58,76,99,59,291,54,349,251,129,818,602,1120,74,0,0,1,2,3,1,5,6,6,7,7,2,4,11,11,16,24,13,9,24,48,19,33,39,63,67,68,78,104,66,284,62,329,240,147,749,649,1132,98,0,0,0,1,2,2,6,11,19,10,0,5,3,8,18,19,24,14,5,18,53,21,41,39,56,79,64,70,93,57,291,42,334,259,143,795,616,1087,71,0,0,0,3,3,4,3,5,6,7,2,3,5,13,14,6,17,21,12,27,40,16,34,39,46,64,78,103,103,63,279,37,314,239,118,805,674,1129,76,1,0,0,4,3,3,7,10,11,8,5,6,3,12,13,18,21,16,18,21,46,21,32,41,77,56,77,103,105,54,269,40,320,247,144,796,621,1098,87,0,0,0,3,2,1,7,12,8,6,5,13,8,11,9,16,23,13,14,22,40,21,53,48,51,59,77,84,126,75,282,48,306,254,151,808,586,1074,76,0,0,0,5,1,3,6,3,7,8,4,3,10,12,14,13,23,12,19,25,43,17,52,42,63,57,92,91,114,61,281,45,342,256,132,812,586,1073,81,0,0,0,1,5,4,4,10,11,9,3,5,5,6,18,21,29,26,14,27,51,17,54,47,51,65,84,84,118,66,291,46,316,244,149,782,579,1080,87,0,0,1,2,5,2,10,17,12,9,0,7,2,10,10,12,20,18,21,27,50,17,50,54,42,82,57,84,103,54,285,41,342,265,115,822,582,1085,118,0,0,0,0,4,3,7,7,11,10,5,6,8,11,18,19,30,34,13,34,47,14,62,49,55,83,82,96,101,51,283,45,346,249,152,843,521,985,73,0,0,0,2,5,6,7,9,11,7,5,4,11,19,13,15,33,18,17,42,57,25,46,65,67,94,68,93,117,67,279,53,306,295,132,844,504,993,72,0,0,1,2,3,5,4,16,13,14,2,8,2,18,19,27,37,27,18,29,57,21,47,57,62,87,81,89,111,57,293,49,319,270,142,858,495,990,78,0,0,1,1,5,3,3,13,10,13,5,7,5,14,15,24,30,23,23,24,57,19,72,49,70,70,72,91,124,60,298,52,347,270,147,841,486,980,71,0,0,0,4,5,3,10,9,10,12,5,9,6,23,14,19,33,27,21,34,60,16,47,57,55,82,84,109,117,44,305,45,335,265,146,856,510,954,80,0,0,0,5,4,5,4,6,10,7,4,0,11,14,19,18,32,25,29,32,75,19,58,56,66,81,79,102,133,52,332,44,306,260,152,879,486,917,80,0,0,0,2,5,2,11,11,13,4,4,5,8,12,15,21,34,27,18,44,58,26,72,62,72,90,84,97,137,51,324,54,332,254,143,857,492,881,78,0,0,0,3,4,1,9,9,3,8,9,9,5,12,20,19,37,30,23,38,69,29,64,51,71,95,92,99,133,52,320,51,340,275,152,868,467,856,73,0,0,0,1,2,3,6,14,19,7,3,3,10,24,15,26,38,27,15,34,71,17,62,72,75,86,84,108,128,65,304,41,356,239,139,864,494,876,100,0,1,1,6,3,6,14,19,11,9,7,11,5,8,25,21,35,16,18,39,61,19,65,42,62,91,83,80,105,38,318,50,372,289,135,847,504,884,72,0,0,1,1,4,2,12,10,17,11,5,3,3,21,25,29,34,34,19,38,55,20,55,59,82,96,99,106,133,45,299,71,339,265,157,822,474,882,73,0,0,0,1,2,5,3,17,16,6,5,7,11,7,16,14,30,31,16,45,71,29,50,62,72,78,77,107,132,62,273,47,366,277,161,892,462,877,91,0,0,0,3,2,2,7,10,6,9,9,6,11,15,17,19,33,20,10,30,54,20,68,48,73,84,72,114,131,60,321,60,356,270,159,874,496,840,92,0,0,1,5,5,4,6,8,7,10,4,7,7,16,26,24,33,20,22,36,49,15,53,65,71,79,80,112,127,63,320,49,359,292,141,837,455,900,105,0,0,1,2,5,4,2,15,8,13,8,6,7,19,24,21,30,22,17,35,53,13,52,61,45,93,74,87,120,60,302,41,331,272,131,877,513,931,117,0,0,0,3,5,3,11,23,24,10,5,7,6,8,13,12,40,18,18,40,41,12,45,57,72,86,71,75,125,68,299,55,302,264,154,874,464,973,120,0,1,0,7,3,4,9,13,19,8,5,3,10,17,25,13,19,18,23,33,49,25,41,51,72,74,56,95,112,60,291,58,281,267,145,916,463,993,89,0,0,1,4,9,13,7,8,7,8,6,8,8,18,20,12,34,26,14,31,50,17,45,65,58,68,77,84,110,66,289,54,284,282,164,871,489,1003,162,0,0,1,3,4,4,14,15,24,17,2,6,9,16,15,20,37,20,12,34,49,12,42,50,54,66,62,81,121,56,265,50,292,258,127,878,506,1015,79,0,0,0,5,1,3,3,13,8,6,0,7,11,15,19,11,17,25,16,34,49,16,37,45,69,72,76,79,101,48,303,38,326,254,140,811,619,1043,78,0,0,0,3,0,4,3,8,5,6,8,6,5,13,18,18,32,19,22,39,43,17,39,45,68,77,74,69,118,47,272,47,332,262,139,833,562,1068,96,0,0,1,3,1,5,5,6,6,8,4,7,3,12,9,18,35,15,24,27,57,20,40,53,70,81,89,91,117,46,262,44,298,251,130,817,588,1059,102,0,0,0,5,0,5,4,10,11,12,3,3,7,8,18,15,22,20,17,20,50,21,46,43,71,70,80,91,110,51,239,34,339,258,119,820,614,1058,100,0,0,0,3,5,3,6,10,12,12,5,5,10,6,21,18,28,14,16,33,38,18,45,56,58,71,65,79,109,57,253,47,310,263,129,854,616,1017,97,0,0,1,4,3,1,5,14,7,11,2,5,2,9,6,19,21,18,21,30,37,22,37,64,40,69,53,89,104,66,281,42,355,233,137,771,615,1095,130,0,0,0,5,2,6,10,10,19,20,5,5,4,12,16,17,28,14,12,25,42,16,42,39,57,61,73,84,110,49,261,48,315,254,125,761,643,1028,108,0,2,1,2,1,5,4,12,13,7,6,7,3,6,14,19,20,22,15,22,52,14,50,45,57,67,72,78,119,51,272,45,284,226,127,831,604,1054,124,0,2,2,0,1,2,5,13,17,10,1,6,4,14,11,19,31,14,14,24,30,12,42,41,54,64,74,82,112,68,250,49,308,261,142,775,557,1060,106,0,1,0,1,4,4,10,9,9,7,0,9,6,8,8,16,21,12,18,24,50,14,43,43,56,55,100,87,109,51,261,51,308,217,139,759,562,1041,120,0,0,0,3,3,2,9,7,12,9,6,4,1,10,9,15,26,11,16,22,35,16,26,45,50,60,56,67,74,62,247,50,282,243,123,747,618,1061,116,0,0,0,1,2,3,2,10,15,10,1,2,6,6,10,9,13,8,14,29,26,12,31,42,59,41,57,88,92,58,257,43,304,236,133,707,612,1016,130,0,0,1,2,4,2,6,8,18,21,3,5,5,7,12,15,17,7,7,23,43,9,28,32,44,42,56,68,83,54,225,38,289,181,133,713,594,991,105,0,1,0,0,5,2,6,9,10,23,1,5,3,3,9,9,30,13,7,18,27,12,28,24,49,42,63,75,81,45,226,43,274,217,147,676,571,925,99,0,0,0,0,3,1,3,5,5,16,3,3,6,7,4,13,15,11,3,10,34,16,20,37,46,41,52,66,85,35,201,45,253,201,119,685,497,913,82,0,0,0,0,0,0,0,0,0,2,0,3,5,3,4,5,13,9,5,11,14,3,35,17,21,41,34,67,67,31,184,49,241,167,93,639,515,797) -mat=matrix(qual,ncol=51,byrow=F) -Lab.palette <- colorRampPalette(c("blue", "orange", "red3","red2","red1","red"), space = "rgb",interpolate=c('spline')) -heatmap(mat,Rowv=NA,Colv=NA,xlab="Position of Read",ylab="Phred Quality Score",labRow=seq(from=33,to=71),col = Lab.palette(256),scale="none" ) -dev.off()
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/output.qual_r Sat Dec 18 19:41:19 2021 +0000 @@ -0,0 +1,62 @@ +pdf('output.qual.boxplot.pdf') +p0<-rep(c(33,37,38,39,40,41,42,43,44,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(119,2,3,2,5,6,8,6,2,3,11,16,6,26,11,13,25,39,7,40,33,33,58,51,116,87,55,256,54,323,263,140,812,654,1119)/1000) +p1<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(105,2,2,2,4,8,6,21,3,1,1,8,13,13,16,16,14,29,32,18,50,30,57,66,73,97,105,60,253,57,330,270,142,801,630,1069)/1000) +p2<-rep(c(33,35,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(109,1,1,3,2,7,11,14,13,2,4,3,8,14,21,27,17,14,26,39,11,37,28,74,64,55,86,106,62,234,56,326,269,147,787,645,1081)/1000) +p3<-rep(c(33,37,38,39,40,41,42,43,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(108,1,6,4,2,9,12,7,3,3,9,14,13,24,20,8,24,46,14,43,28,59,67,75,88,107,51,285,56,293,239,139,802,660,1084)/1000) +p4<-rep(c(33,35,37,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(97,1,1,3,9,8,11,5,4,2,4,10,16,19,24,7,8,35,43,19,49,29,51,67,51,93,107,43,306,65,345,223,123,789,661,1075)/1000) +p5<-rep(c(33,37,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(96,3,2,5,11,6,8,2,7,2,12,17,15,16,12,11,25,31,12,32,36,59,70,69,74,99,56,277,59,343,249,111,845,650,1081)/1000) +p6<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(86,2,4,2,6,12,8,10,1,7,7,9,11,14,26,14,9,14,53,17,34,41,55,71,76,76,117,62,238,62,339,229,155,798,607,1131)/1000) +p7<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(76,1,4,4,6,11,9,13,5,5,6,6,17,19,20,17,8,19,45,15,30,33,60,68,58,76,99,59,291,54,349,251,129,818,602,1120)/1000) +p8<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(74,1,2,3,1,5,6,6,7,7,2,4,11,11,16,24,13,9,24,48,19,33,39,63,67,68,78,104,66,284,62,329,240,147,749,649,1132)/1000) +p9<-rep(c(33,37,38,39,40,41,42,43,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(98,1,2,2,6,11,19,10,5,3,8,18,19,24,14,5,18,53,21,41,39,56,79,64,70,93,57,291,42,334,259,143,795,616,1087)/1000) +p10<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(71,3,3,4,3,5,6,7,2,3,5,13,14,6,17,21,12,27,40,16,34,39,46,64,78,103,103,63,279,37,314,239,118,805,674,1129)/1000) +p11<-rep(c(33,34,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(76,1,4,3,3,7,10,11,8,5,6,3,12,13,18,21,16,18,21,46,21,32,41,77,56,77,103,105,54,269,40,320,247,144,796,621,1098)/1000) +p12<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(87,3,2,1,7,12,8,6,5,13,8,11,9,16,23,13,14,22,40,21,53,48,51,59,77,84,126,75,282,48,306,254,151,808,586,1074)/1000) +p13<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(76,5,1,3,6,3,7,8,4,3,10,12,14,13,23,12,19,25,43,17,52,42,63,57,92,91,114,61,281,45,342,256,132,812,586,1073)/1000) +p14<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(81,1,5,4,4,10,11,9,3,5,5,6,18,21,29,26,14,27,51,17,54,47,51,65,84,84,118,66,291,46,316,244,149,782,579,1080)/1000) +p15<-rep(c(33,36,37,38,39,40,41,42,43,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(87,1,2,5,2,10,17,12,9,7,2,10,10,12,20,18,21,27,50,17,50,54,42,82,57,84,103,54,285,41,342,265,115,822,582,1085)/1000) +p16<-rep(c(33,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(118,4,3,7,7,11,10,5,6,8,11,18,19,30,34,13,34,47,14,62,49,55,83,82,96,101,51,283,45,346,249,152,843,521,985)/1000) +p17<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(73,2,5,6,7,9,11,7,5,4,11,19,13,15,33,18,17,42,57,25,46,65,67,94,68,93,117,67,279,53,306,295,132,844,504,993)/1000) +p18<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(72,1,2,3,5,4,16,13,14,2,8,2,18,19,27,37,27,18,29,57,21,47,57,62,87,81,89,111,57,293,49,319,270,142,858,495,990)/1000) +p19<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(78,1,1,5,3,3,13,10,13,5,7,5,14,15,24,30,23,23,24,57,19,72,49,70,70,72,91,124,60,298,52,347,270,147,841,486,980)/1000) +p20<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(71,4,5,3,10,9,10,12,5,9,6,23,14,19,33,27,21,34,60,16,47,57,55,82,84,109,117,44,305,45,335,265,146,856,510,954)/1000) +p21<-rep(c(33,37,38,39,40,41,42,43,44,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(80,5,4,5,4,6,10,7,4,11,14,19,18,32,25,29,32,75,19,58,56,66,81,79,102,133,52,332,44,306,260,152,879,486,917)/1000) +p22<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(80,2,5,2,11,11,13,4,4,5,8,12,15,21,34,27,18,44,58,26,72,62,72,90,84,97,137,51,324,54,332,254,143,857,492,881)/1000) +p23<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(78,3,4,1,9,9,3,8,9,9,5,12,20,19,37,30,23,38,69,29,64,51,71,95,92,99,133,52,320,51,340,275,152,868,467,856)/1000) +p24<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(73,1,2,3,6,14,19,7,3,3,10,24,15,26,38,27,15,34,71,17,62,72,75,86,84,108,128,65,304,41,356,239,139,864,494,876)/1000) +p25<-rep(c(33,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(100,1,1,6,3,6,14,19,11,9,7,11,5,8,25,21,35,16,18,39,61,19,65,42,62,91,83,80,105,38,318,50,372,289,135,847,504,884)/1000) +p26<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(72,1,1,4,2,12,10,17,11,5,3,3,21,25,29,34,34,19,38,55,20,55,59,82,96,99,106,133,45,299,71,339,265,157,822,474,882)/1000) +p27<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(73,1,2,5,3,17,16,6,5,7,11,7,16,14,30,31,16,45,71,29,50,62,72,78,77,107,132,62,273,47,366,277,161,892,462,877)/1000) +p28<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(91,3,2,2,7,10,6,9,9,6,11,15,17,19,33,20,10,30,54,20,68,48,73,84,72,114,131,60,321,60,356,270,159,874,496,840)/1000) +p29<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(92,1,5,5,4,6,8,7,10,4,7,7,16,26,24,33,20,22,36,49,15,53,65,71,79,80,112,127,63,320,49,359,292,141,837,455,900)/1000) +p30<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(105,1,2,5,4,2,15,8,13,8,6,7,19,24,21,30,22,17,35,53,13,52,61,45,93,74,87,120,60,302,41,331,272,131,877,513,931)/1000) +p31<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(117,3,5,3,11,23,24,10,5,7,6,8,13,12,40,18,18,40,41,12,45,57,72,86,71,75,125,68,299,55,302,264,154,874,464,973)/1000) +p32<-rep(c(33,35,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(120,1,7,3,4,9,13,19,8,5,3,10,17,25,13,19,18,23,33,49,25,41,51,72,74,56,95,112,60,291,58,281,267,145,916,463,993)/1000) +p33<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(89,1,4,9,13,7,8,7,8,6,8,8,18,20,12,34,26,14,31,50,17,45,65,58,68,77,84,110,66,289,54,284,282,164,871,489,1003)/1000) +p34<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(162,1,3,4,4,14,15,24,17,2,6,9,16,15,20,37,20,12,34,49,12,42,50,54,66,62,81,121,56,265,50,292,258,127,878,506,1015)/1000) +p35<-rep(c(33,37,38,39,40,41,42,43,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(79,5,1,3,3,13,8,6,7,11,15,19,11,17,25,16,34,49,16,37,45,69,72,76,79,101,48,303,38,326,254,140,811,619,1043)/1000) +p36<-rep(c(33,37,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(78,3,4,3,8,5,6,8,6,5,13,18,18,32,19,22,39,43,17,39,45,68,77,74,69,118,47,272,47,332,262,139,833,562,1068)/1000) +p37<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(96,1,3,1,5,5,6,6,8,4,7,3,12,9,18,35,15,24,27,57,20,40,53,70,81,89,91,117,46,262,44,298,251,130,817,588,1059)/1000) +p38<-rep(c(33,37,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(102,5,5,4,10,11,12,3,3,7,8,18,15,22,20,17,20,50,21,46,43,71,70,80,91,110,51,239,34,339,258,119,820,614,1058)/1000) +p39<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(100,3,5,3,6,10,12,12,5,5,10,6,21,18,28,14,16,33,38,18,45,56,58,71,65,79,109,57,253,47,310,263,129,854,616,1017)/1000) +p40<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(97,1,4,3,1,5,14,7,11,2,5,2,9,6,19,21,18,21,30,37,22,37,64,40,69,53,89,104,66,281,42,355,233,137,771,615,1095)/1000) +p41<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(130,5,2,6,10,10,19,20,5,5,4,12,16,17,28,14,12,25,42,16,42,39,57,61,73,84,110,49,261,48,315,254,125,761,643,1028)/1000) +p42<-rep(c(33,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(108,2,1,2,1,5,4,12,13,7,6,7,3,6,14,19,20,22,15,22,52,14,50,45,57,67,72,78,119,51,272,45,284,226,127,831,604,1054)/1000) +p43<-rep(c(33,35,36,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(124,2,2,1,2,5,13,17,10,1,6,4,14,11,19,31,14,14,24,30,12,42,41,54,64,74,82,112,68,250,49,308,261,142,775,557,1060)/1000) +p44<-rep(c(33,35,37,38,39,40,41,42,43,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(106,1,1,4,4,10,9,9,7,9,6,8,8,16,21,12,18,24,50,14,43,43,56,55,100,87,109,51,261,51,308,217,139,759,562,1041)/1000) +p45<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(120,3,3,2,9,7,12,9,6,4,1,10,9,15,26,11,16,22,35,16,26,45,50,60,56,67,74,62,247,50,282,243,123,747,618,1061)/1000) +p46<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(116,1,2,3,2,10,15,10,1,2,6,6,10,9,13,8,14,29,26,12,31,42,59,41,57,88,92,58,257,43,304,236,133,707,612,1016)/1000) +p47<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(130,1,2,4,2,6,8,18,21,3,5,5,7,12,15,17,7,7,23,43,9,28,32,44,42,56,68,83,54,225,38,289,181,133,713,594,991)/1000) +p48<-rep(c(33,35,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(105,1,5,2,6,9,10,23,1,5,3,3,9,9,30,13,7,18,27,12,28,24,49,42,63,75,81,45,226,43,274,217,147,676,571,925)/1000) +p49<-rep(c(33,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(99,3,1,3,5,5,16,3,3,6,7,4,13,15,11,3,10,34,16,20,37,46,41,52,66,85,35,201,45,253,201,119,685,497,913)/1000) +p50<-rep(c(33,43,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(82,2,3,5,3,4,5,13,9,5,11,14,3,35,17,21,41,34,67,67,31,184,49,241,167,93,639,515,797)/1000) +boxplot(p0,p1,p2,p3,p4,p5,p6,p7,p8,p9,p10,p11,p12,p13,p14,p15,p16,p17,p18,p19,p20,p21,p22,p23,p24,p25,p26,p27,p28,p29,p30,p31,p32,p33,p34,p35,p36,p37,p38,p39,p40,p41,p42,p43,p44,p45,p46,p47,p48,p49,p50,xlab="Position of Read(5'->3')",ylab="Phred Quality Score",outline=F) +dev.off() + + +pdf('output.qual.heatmap.pdf') +qual=c(119,0,0,0,2,3,2,5,6,8,6,2,0,3,11,16,6,26,11,13,25,39,7,40,33,33,58,51,116,87,55,256,54,323,263,140,812,654,1119,105,0,0,0,2,2,2,4,8,6,21,3,1,1,8,13,13,16,16,14,29,32,18,50,30,57,66,73,97,105,60,253,57,330,270,142,801,630,1069,109,0,1,0,1,3,2,7,11,14,13,2,4,3,8,14,21,27,17,14,26,39,11,37,28,74,64,55,86,106,62,234,56,326,269,147,787,645,1081,108,0,0,0,1,6,4,2,9,12,7,0,3,3,9,14,13,24,20,8,24,46,14,43,28,59,67,75,88,107,51,285,56,293,239,139,802,660,1084,97,0,1,0,1,0,3,9,8,11,5,4,2,4,10,16,19,24,7,8,35,43,19,49,29,51,67,51,93,107,43,306,65,345,223,123,789,661,1075,96,0,0,0,3,0,2,5,11,6,8,2,7,2,12,17,15,16,12,11,25,31,12,32,36,59,70,69,74,99,56,277,59,343,249,111,845,650,1081,86,0,0,0,2,4,2,6,12,8,10,1,7,7,9,11,14,26,14,9,14,53,17,34,41,55,71,76,76,117,62,238,62,339,229,155,798,607,1131,76,0,0,0,1,4,4,6,11,9,13,5,5,6,6,17,19,20,17,8,19,45,15,30,33,60,68,58,76,99,59,291,54,349,251,129,818,602,1120,74,0,0,1,2,3,1,5,6,6,7,7,2,4,11,11,16,24,13,9,24,48,19,33,39,63,67,68,78,104,66,284,62,329,240,147,749,649,1132,98,0,0,0,1,2,2,6,11,19,10,0,5,3,8,18,19,24,14,5,18,53,21,41,39,56,79,64,70,93,57,291,42,334,259,143,795,616,1087,71,0,0,0,3,3,4,3,5,6,7,2,3,5,13,14,6,17,21,12,27,40,16,34,39,46,64,78,103,103,63,279,37,314,239,118,805,674,1129,76,1,0,0,4,3,3,7,10,11,8,5,6,3,12,13,18,21,16,18,21,46,21,32,41,77,56,77,103,105,54,269,40,320,247,144,796,621,1098,87,0,0,0,3,2,1,7,12,8,6,5,13,8,11,9,16,23,13,14,22,40,21,53,48,51,59,77,84,126,75,282,48,306,254,151,808,586,1074,76,0,0,0,5,1,3,6,3,7,8,4,3,10,12,14,13,23,12,19,25,43,17,52,42,63,57,92,91,114,61,281,45,342,256,132,812,586,1073,81,0,0,0,1,5,4,4,10,11,9,3,5,5,6,18,21,29,26,14,27,51,17,54,47,51,65,84,84,118,66,291,46,316,244,149,782,579,1080,87,0,0,1,2,5,2,10,17,12,9,0,7,2,10,10,12,20,18,21,27,50,17,50,54,42,82,57,84,103,54,285,41,342,265,115,822,582,1085,118,0,0,0,0,4,3,7,7,11,10,5,6,8,11,18,19,30,34,13,34,47,14,62,49,55,83,82,96,101,51,283,45,346,249,152,843,521,985,73,0,0,0,2,5,6,7,9,11,7,5,4,11,19,13,15,33,18,17,42,57,25,46,65,67,94,68,93,117,67,279,53,306,295,132,844,504,993,72,0,0,1,2,3,5,4,16,13,14,2,8,2,18,19,27,37,27,18,29,57,21,47,57,62,87,81,89,111,57,293,49,319,270,142,858,495,990,78,0,0,1,1,5,3,3,13,10,13,5,7,5,14,15,24,30,23,23,24,57,19,72,49,70,70,72,91,124,60,298,52,347,270,147,841,486,980,71,0,0,0,4,5,3,10,9,10,12,5,9,6,23,14,19,33,27,21,34,60,16,47,57,55,82,84,109,117,44,305,45,335,265,146,856,510,954,80,0,0,0,5,4,5,4,6,10,7,4,0,11,14,19,18,32,25,29,32,75,19,58,56,66,81,79,102,133,52,332,44,306,260,152,879,486,917,80,0,0,0,2,5,2,11,11,13,4,4,5,8,12,15,21,34,27,18,44,58,26,72,62,72,90,84,97,137,51,324,54,332,254,143,857,492,881,78,0,0,0,3,4,1,9,9,3,8,9,9,5,12,20,19,37,30,23,38,69,29,64,51,71,95,92,99,133,52,320,51,340,275,152,868,467,856,73,0,0,0,1,2,3,6,14,19,7,3,3,10,24,15,26,38,27,15,34,71,17,62,72,75,86,84,108,128,65,304,41,356,239,139,864,494,876,100,0,1,1,6,3,6,14,19,11,9,7,11,5,8,25,21,35,16,18,39,61,19,65,42,62,91,83,80,105,38,318,50,372,289,135,847,504,884,72,0,0,1,1,4,2,12,10,17,11,5,3,3,21,25,29,34,34,19,38,55,20,55,59,82,96,99,106,133,45,299,71,339,265,157,822,474,882,73,0,0,0,1,2,5,3,17,16,6,5,7,11,7,16,14,30,31,16,45,71,29,50,62,72,78,77,107,132,62,273,47,366,277,161,892,462,877,91,0,0,0,3,2,2,7,10,6,9,9,6,11,15,17,19,33,20,10,30,54,20,68,48,73,84,72,114,131,60,321,60,356,270,159,874,496,840,92,0,0,1,5,5,4,6,8,7,10,4,7,7,16,26,24,33,20,22,36,49,15,53,65,71,79,80,112,127,63,320,49,359,292,141,837,455,900,105,0,0,1,2,5,4,2,15,8,13,8,6,7,19,24,21,30,22,17,35,53,13,52,61,45,93,74,87,120,60,302,41,331,272,131,877,513,931,117,0,0,0,3,5,3,11,23,24,10,5,7,6,8,13,12,40,18,18,40,41,12,45,57,72,86,71,75,125,68,299,55,302,264,154,874,464,973,120,0,1,0,7,3,4,9,13,19,8,5,3,10,17,25,13,19,18,23,33,49,25,41,51,72,74,56,95,112,60,291,58,281,267,145,916,463,993,89,0,0,1,4,9,13,7,8,7,8,6,8,8,18,20,12,34,26,14,31,50,17,45,65,58,68,77,84,110,66,289,54,284,282,164,871,489,1003,162,0,0,1,3,4,4,14,15,24,17,2,6,9,16,15,20,37,20,12,34,49,12,42,50,54,66,62,81,121,56,265,50,292,258,127,878,506,1015,79,0,0,0,5,1,3,3,13,8,6,0,7,11,15,19,11,17,25,16,34,49,16,37,45,69,72,76,79,101,48,303,38,326,254,140,811,619,1043,78,0,0,0,3,0,4,3,8,5,6,8,6,5,13,18,18,32,19,22,39,43,17,39,45,68,77,74,69,118,47,272,47,332,262,139,833,562,1068,96,0,0,1,3,1,5,5,6,6,8,4,7,3,12,9,18,35,15,24,27,57,20,40,53,70,81,89,91,117,46,262,44,298,251,130,817,588,1059,102,0,0,0,5,0,5,4,10,11,12,3,3,7,8,18,15,22,20,17,20,50,21,46,43,71,70,80,91,110,51,239,34,339,258,119,820,614,1058,100,0,0,0,3,5,3,6,10,12,12,5,5,10,6,21,18,28,14,16,33,38,18,45,56,58,71,65,79,109,57,253,47,310,263,129,854,616,1017,97,0,0,1,4,3,1,5,14,7,11,2,5,2,9,6,19,21,18,21,30,37,22,37,64,40,69,53,89,104,66,281,42,355,233,137,771,615,1095,130,0,0,0,5,2,6,10,10,19,20,5,5,4,12,16,17,28,14,12,25,42,16,42,39,57,61,73,84,110,49,261,48,315,254,125,761,643,1028,108,0,2,1,2,1,5,4,12,13,7,6,7,3,6,14,19,20,22,15,22,52,14,50,45,57,67,72,78,119,51,272,45,284,226,127,831,604,1054,124,0,2,2,0,1,2,5,13,17,10,1,6,4,14,11,19,31,14,14,24,30,12,42,41,54,64,74,82,112,68,250,49,308,261,142,775,557,1060,106,0,1,0,1,4,4,10,9,9,7,0,9,6,8,8,16,21,12,18,24,50,14,43,43,56,55,100,87,109,51,261,51,308,217,139,759,562,1041,120,0,0,0,3,3,2,9,7,12,9,6,4,1,10,9,15,26,11,16,22,35,16,26,45,50,60,56,67,74,62,247,50,282,243,123,747,618,1061,116,0,0,0,1,2,3,2,10,15,10,1,2,6,6,10,9,13,8,14,29,26,12,31,42,59,41,57,88,92,58,257,43,304,236,133,707,612,1016,130,0,0,1,2,4,2,6,8,18,21,3,5,5,7,12,15,17,7,7,23,43,9,28,32,44,42,56,68,83,54,225,38,289,181,133,713,594,991,105,0,1,0,0,5,2,6,9,10,23,1,5,3,3,9,9,30,13,7,18,27,12,28,24,49,42,63,75,81,45,226,43,274,217,147,676,571,925,99,0,0,0,0,3,1,3,5,5,16,3,3,6,7,4,13,15,11,3,10,34,16,20,37,46,41,52,66,85,35,201,45,253,201,119,685,497,913,82,0,0,0,0,0,0,0,0,0,2,0,3,5,3,4,5,13,9,5,11,14,3,35,17,21,41,34,67,67,31,184,49,241,167,93,639,515,797) +mat=matrix(qual,ncol=51,byrow=F) +Lab.palette <- colorRampPalette(c("blue", "orange", "red3","red2","red1","red"), space = "rgb",interpolate=c('spline')) +heatmap(mat,Rowv=NA,Colv=NA,xlab="Position of Read",ylab="Phred Quality Score",labRow=seq(from=33,to=71),col = Lab.palette(256),scale="none" ) +dev.off()
--- a/test-data/output2.geneBodyCoverage.r Thu Nov 28 15:56:37 2019 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,21 +0,0 @@ -pairend_strandspecific_51mer_hg19_chr1_1_100000_bam <- c(0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0) -pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.1 <- c(0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0) -pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.2 <- c(0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0) -data_matrix <- matrix(c(pairend_strandspecific_51mer_hg19_chr1_1_100000_bam,pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.1,pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.2), byrow=T, ncol=100) -rowLabel <- c("pairend_strandspecific_51mer_hg19_chr1_1_100000_bam","pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.1","pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.2") - - -pdf("output.geneBodyCoverage.heatMap.pdf") -rc <- cm.colors(ncol(data_matrix)) -heatmap(data_matrix, scale=c("none"),keep.dendro=F, labRow = rowLabel ,Colv = NA,Rowv = NA,labCol=NA,col=cm.colors(256),margins = c(6, 8),ColSideColors = rc,cexRow=1,cexCol=1,xlab="Gene body percentile (5'->3')", add.expr=x_axis_expr <- axis(side=1,at=c(1,10,20,30,40,50,60,70,80,90,100),labels=c("1","10","20","30","40","50","60","70","80","90","100"))) -dev.off() - - -pdf("output.geneBodyCoverage.curves.pdf") -x=1:100 -icolor = colorRampPalette(c("#7fc97f","#beaed4","#fdc086","#ffff99","#386cb0","#f0027f"))(3) -plot(x,pairend_strandspecific_51mer_hg19_chr1_1_100000_bam,type='l',xlab="Gene body percentile (5'->3')", ylab="Coverage",lwd=0.8,col=icolor[1]) -lines(x,pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.1,type='l',col=icolor[2]) -lines(x,pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.2,type='l',col=icolor[3]) -legend(0,1,fill=icolor[1:3], legend=c('pairend_strandspecific_51mer_hg19_chr1_1_100000_bam','pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.1','pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.2')) -dev.off()
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/output2.geneBodyCoverage_r Sat Dec 18 19:41:19 2021 +0000 @@ -0,0 +1,21 @@ +pairend_strandspecific_51mer_hg19_chr1_1_100000_bam <- c(0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0) +pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.1 <- c(0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0) +pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.2 <- c(0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0) +data_matrix <- matrix(c(pairend_strandspecific_51mer_hg19_chr1_1_100000_bam,pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.1,pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.2), byrow=T, ncol=100) +rowLabel <- c("pairend_strandspecific_51mer_hg19_chr1_1_100000_bam","pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.1","pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.2") + + +pdf("output.geneBodyCoverage.heatMap.pdf") +rc <- cm.colors(ncol(data_matrix)) +heatmap(data_matrix, scale=c("none"),keep.dendro=F, labRow = rowLabel ,Colv = NA,Rowv = NA,labCol=NA,col=cm.colors(256),margins = c(6, 8),ColSideColors = rc,cexRow=1,cexCol=1,xlab="Gene body percentile (5'->3')", add.expr=x_axis_expr <- axis(side=1,at=c(1,10,20,30,40,50,60,70,80,90,100),labels=c("1","10","20","30","40","50","60","70","80","90","100"))) +dev.off() + + +pdf("output.geneBodyCoverage.curves.pdf") +x=1:100 +icolor = colorRampPalette(c("#7fc97f","#beaed4","#fdc086","#ffff99","#386cb0","#f0027f"))(3) +plot(x,pairend_strandspecific_51mer_hg19_chr1_1_100000_bam,type='l',xlab="Gene body percentile (5'->3')", ylab="Coverage",lwd=0.8,col=icolor[1]) +lines(x,pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.1,type='l',col=icolor[2]) +lines(x,pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.2,type='l',col=icolor[3]) +legend(0,1,fill=icolor[1:3], legend=c('pairend_strandspecific_51mer_hg19_chr1_1_100000_bam','pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.1','pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.2')) +dev.off()
--- a/tin.xml Thu Nov 28 15:56:37 2019 -0500 +++ b/tin.xml Sat Dec 18 19:41:19 2021 +0000 @@ -1,8 +1,8 @@ -<tool id="rseqc_tin" name="Transcript Integrity Number" version="@WRAPPER_VERSION@.1"> +<tool id="rseqc_tin" name="Transcript Integrity Number" version="@TOOL_VERSION@.1"> <description> evaluates RNA integrity at a transcript level </description> - + <expand macro="bio_tools"/> <macros> <import>rseqc_macros.xml</import> </macros> @@ -49,7 +49,7 @@ <tests> <test> <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/> - <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed"/> + <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" ftype="bed12"/> <output name="outputsummary"> <assert_contents> <has_line_matching expression="^Bam_file\tTIN\(mean\)\tTIN\(median\)\tTIN\(stdev\)$" />