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annotate tin.xml @ 58:1a052c827e88 draft

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"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/rseqc commit 57f71aa633a43ab02bbf05acd0c6d7f406e01f1e"
author iuc
date Thu, 28 Nov 2019 15:56:37 -0500
parents f437057e46f1
children dbedfc5f5a3c
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1 <tool id="rseqc_tin" name="Transcript Integrity Number" version="@WRAPPER_VERSION@.1">
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2 <description>
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3 evaluates RNA integrity at a transcript level
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4 </description>
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6 <macros>
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7 <import>rseqc_macros.xml</import>
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8 </macros>
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10 <expand macro="requirements" />
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12 <expand macro="stdio" />
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14 <version_command><![CDATA[tin.py --version]]></version_command>
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16 <!-- Generate output files here because tin.py removes all instances of "bam"
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17 in the filename -->
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18 <command><![CDATA[
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19 #import re
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20 ln -sf '${input}' 'input.bam' &&
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21 ln -sf '${input.metadata.bam_index}' 'input.bam.bai' &&
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22 tin.py -i 'input.bam' --refgene='${refgene}' --minCov=${minCov}
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23 --sample-size=${samplesize} ${subtractbackground}
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24 ]]>
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25 </command>
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27 <inputs>
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28 <expand macro="bam_param" />
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29 <expand macro="refgene_param" />
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30 <param name="minCov" type="integer" value="10" label="Minimum coverage (default=10)"
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31 help="Minimum number of reads mapped to a transcript (--minCov)." />
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32 <param name="samplesize" type="integer" value="100" label="Sample size (default=100)"
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33 help="Number of equal-spaced nucleotide positions picked from mRNA.
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34 Note: if this number is larger than the length of mRNA (L), it will
09846d5169fa planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/rseqc commit 37fb1988971807c6a072e1afd98eeea02329ee83
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35 be halved until is's smaller than L. (--sample-size)." />
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36 <param name="subtractbackground" type="boolean" value="false" falsevalue=""
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37 truevalue="--subtract-background" label="Subtract background noise
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38 (default=No)" help="Subtract background noise (estimated from
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39 intronic reads). Only use this option if there are substantial
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40 intronic reads (--subtract-background)." />
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41 </inputs>
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43 <outputs>
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44 <data name="outputsummary" format="tabular" from_work_dir="input.summary.txt" label="TIN on ${on_string} (summary)" />
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45 <data name="outputxls" format="xls" from_work_dir="input.tin.xls" label="TIN on ${on_string} (tin)" />
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46 </outputs>
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48 <!-- PDF Files contain R version, must avoid checking for diff -->
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49 <tests>
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50 <test>
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51 <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
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52 <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed"/>
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53 <output name="outputsummary">
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54 <assert_contents>
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55 <has_line_matching expression="^Bam_file\tTIN\(mean\)\tTIN\(median\)\tTIN\(stdev\)$" />
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56 <has_line_matching expression="^input\.bam\t8\.8709677419\d+\t8\.8709677419\d+\t0\.0$" />
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57 </assert_contents>
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58 </output>
51
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59 <output name="outputxls" file="output.tin.xls"/>
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60 </test>
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61 </tests>
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63 <help><![CDATA[
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64 ## tin.py
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65
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66 This program is designed to evaluate RNA integrity at transcript level. TIN
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67 (transcript integrity number) is named in analogous to RIN (RNA integrity
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68 number). RIN (RNA integrity number) is the most widely used metric to
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69 evaluate RNA integrity at sample (or transcriptome) level. It is a very
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70 useful preventive measure to ensure good RNA quality and robust,
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71 reproducible RNA sequencing. However, it has several weaknesses:
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72
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73 * RIN score (1 <= RIN <= 10) is not a direct measurement of mRNA quality.
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74 RIN score heavily relies on the amount of 18S and 28S ribosome RNAs, which
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75 was demonstrated by the four features used by the RIN algorithm: the
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76 “total RNA ratio” (i.e. the fraction of the area in the region of 18S and
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77 28S compared to the total area under the curve), 28S-region height, 28S
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78 area ratio and the 18S:28S ratio24. To a large extent, RIN score was a
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79 measure of ribosome RNA integrity. However, in most RNA-seq experiments,
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80 ribosome RNAs were depleted from the library to enrich mRNA through either
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81 ribo-minus or polyA selection procedure.
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82
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83 * RIN only measures the overall RNA quality of an RNA sample. However, in real
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84 situation, the degradation rate may differs significantly among
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85 transcripts, depending on factors such as “AU-rich sequence”, “transcript
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86 length”, “GC content”, “secondary structure” and the “RNA-protein
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87 complex”. Therefore, RIN is practically not very useful in downstream
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88 analysis such as adjusting the gene expression count.
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89
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90 * RIN has very limited sensitivity to measure substantially degraded RNA
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91 samples such as preserved clinical tissues. (ref:
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92 https://www.scribd.com/document/352764986/DV200-Technote-Truseq-Rna-Access).
51
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93
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94 To overcome these limitations, we developed TIN, an algorithm that is able
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95 to measure RNA integrity at transcript level. TIN calculates a score (0 <=
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96 TIN <= 100) for each expressed transcript, however, the medTIN (i.e.
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97 meidan TIN score across all the transcripts) can also be used to measure
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98 the RNA integrity at sample level. Below plots demonstrated TIN is a
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99 useful metric to measure RNA integrity in both transcriptome-wise and
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100 transcript-wise, as demonstrated by the high concordance with both RIN and
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101 RNA fragment size (estimated from RNA-seq read pairs).
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102
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103
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104 ## Inputs
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105
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106 Input BAM/SAM file
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107 Alignment file in BAM/SAM format.
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108
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109 Reference gene model
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110 Gene Model in BED format. Must be standard 12-column BED file.
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111
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112 Minimum coverage
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113 Minimum number of reads mapped to a tracript (default is 10).
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114
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115 Sample size
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116 Number of equal-spaced nucleotide positions picked from mRNA. Note: if
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117 this number is larger than the length of mRNA (L), it will be halved until
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118 it’s smaller than L (default is 100).
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119
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120 Subtract background
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121 Subtract background noise (estimated from intronic reads). Only use this
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122 option if there are substantial intronic reads.
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123
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124
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125 ## Outputs
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126
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127 Text
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128 Table that includes the gene identifier (geneID), chromosome (chrom),
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129 transcript start (tx_start), transcript end (tx_end), and transcript
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130 integrity number (TIN).
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131
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132 Example output:
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133
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134 ------ ----- ---------- --------- -------------
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135 geneID chrom tx_start tx_end TIN
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136 ------ ----- ---------- --------- -------------
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137 ABCC2 chr10 101542354 101611949 67.6446525761
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138 IPMK chr10 59951277 60027694 86.383618429
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139 RUFY2 chr10 70100863 70167051 43.8967503948
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140 ------ ----- ---------- --------- -------------
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141
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142 @ABOUT@
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143
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144 ]]>
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145 </help>
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146
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147 <expand macro="citations" />
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148
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149 </tool>